# ICCV2021-Papers-with-Code **Repository Path**: PythonIoT/ICCV2021-Papers-with-Code ## Basic Information - **Project Name**: ICCV2021-Papers-with-Code - **Description**: No description available - **Primary Language**: Unknown - **License**: Not specified - **Default Branch**: main - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 1 - **Forks**: 0 - **Created**: 2021-09-21 - **Last Updated**: 2022-11-07 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # ICCV2021-Papers-with-Code [ICCV 2021](http://iccv2021.thecvf.com/) 论文和开源项目合集(papers with code)！ 1617 papers accepted - 25.9% acceptance rate ICCV 2021 收录论文IDs：https://docs.google.com/spreadsheets/u/1/d/e/2PACX-1vRfaTmsNweuaA0Gjyu58H_Cx56pGwFhcTYII0u1pg0U7MbhlgY0R6Y-BbK3xFhAiwGZ26u3TAtN5MnS/pubhtml > 注1：欢迎各位大佬提交issue，分享ICCV 2021论文和开源项目！ > > 注2：关于往年CV顶会论文以及其他优质CV论文和大盘点，详见： https://github.com/amusi/daily-paper-computer-vision ## 【ICCV 2021 论文和开源目录】 - [Backbone](#Backbone) - [Transformer](#Transformer) - [涨点神器](#Cool) - [GAN](#GAN) - [NAS](#NAS) - [NeRF](#NeRF) - [Loss](#Loss) - [Zero-Shot Learning](#Zero-Shot-Learning) - [Few-Shot Learning](#Few-Shot-Learning) - [长尾(Long-tailed)](#Long-tailed) - [Vision and Language](#VL) - [无监督/自监督(Self-Supervised)](#Un/Self-Supervised) - [Multi-Label Image Recognition(多标签图像识别)](#MLIR) - [2D目标检测(Object Detection)](#Object-Detection) - [语义分割(Semantic Segmentation)](#Semantic-Segmentation) - [实例分割(Instance Segmentation)](#Instance-Segmentation) - [医学图像分割(Medical Image Segmentation)](#Medical-Image-Segmentation) - [视频目标分割(Video Object Segmentation)](#VOS) - [Few-shot Segmentation](#Few-shot-Segmentation) - [人体运动分割(Human Motion Segmentation)](#HMS) - [目标跟踪(Object Tracking)](#Object-Tracking) - [3D Point Cloud](#3D-Point-Cloud) - [3D Object Detection(3D目标检测)](#Point-Cloud-Object-Detection) - [3D Semantic Segmenation(3D语义分割)](#Point-Cloud-Semantic-Segmentation) - [3D Instance Segmentation(3D实例分割)](#Point-Cloud-Instance-Segmentation) - [3D Multi-Object Tracking(3D多目标跟踪)](#Point-Cloud-Multi-Object-Tracking) - [Point Cloud Denoising(点云去噪)](#Point-Cloud-Denoising) - [Point Cloud Registration(点云配准)](#Point-Cloud-Registration) - [Point Cloud Completion(点云补全)](#PCC) - [雷达语义分割(Radar Semantic Segmentation)](#RSS) - [图像恢复(Image Restoration)](#Image-Restoration) - [超分辨率(Super-Resolution)](#Super-Resolution) - [去噪(Denoising)](#Denoising) - [医学图像去噪(Medical Image Denoising)](#Medical-Image-Denoising) - [去模糊(Deblurring)](#Deblurring) - [阴影去除(Shadow Removal)](Shadow-Removal) - [视频插帧(Video Frame Interpolation)](#VFI) - [视频修复/补全(Video Inpainting)](#Video-Inpainting) - [行人重识别(Person Re-identification)](#Re-ID) - [行人搜索(Person Search)](#Person-Search) - [2D/3D人体姿态估计(2D/3D Human Pose Estimation)](#Human-Pose-Estimation) - [3D人头重建(3D Head Reconstruction)](#3D-Head-Reconstruction) - [人脸识别(Face Recognition)](#FR) - [人脸表情识别(Facial Expression Recognition)](#FER) - [行为识别(Action Recognition)](#Action-Recognition) - [时序动作定位(Temporal Action Localization)](#Temporal-Action-Localization) - [动作检测(Action Detection)](Action-Detection) - [群体活动识别(Group Activity Recognition)](#GAR) - [手语识别(Sign Language Recognition)](#SLR) - [文本检测(Text Detection)](#Text-Detection) - [文本识别(Text Recognition)](#Text-Recognition) - [文本替换(Text Repalcement)](#TR) - [视觉问答(Visual Question Answering, VQA)](#Visual-Question-Answering) - [对抗攻击(Adversarial Attack)](#Adversarial-Attack) - [深度估计(Depth Estimation)](#Depth-Estimation) - [视线估计(Gaze Estimation)](#Gaze-Estimation) - [人群计数(Crowd Counting)](#Crowd-Counting) - [车道线检测(Lane Detection)](#Lane-Detection) - [轨迹预测(Trajectory Prediction)](#Trajectory-Prediction) - [异常检测(Anomaly Detection)](#Anomaly-Detection) - [场景图生成(Scene Graph Generation)](#Scene-Graph-Generation) - [图像编辑(Image Editing)](#Image-Editing) - [图像合成(Image Synthesis)](#Image-Synthesis) - [图像检索(Image Retrieval)](#Image-Retrieval) - [三维重建(3D Reconstruction)](#3D-R) - [视频稳像(Video Stabilization)](#Video-Stabilization) - [细粒度识别(Fine-Grained Recognition)](#FGR) - [风格迁移(Style Transfer)](#Style-Transfer) - [神经绘画(Neural Painting)](#Neural-Painting) - [特征匹配(Feature Matching)](#FM) - [语义对应(Semantic Correspondence)](#Semantic-Correspondence) - [边缘检测(Edge Detection)](#Edge-Detection) - [相机标定(Camera Calibration)](#Camera-Calibration) - [图像质量评估(Image Quality Assessment)](#IQA) - [度量学习(Metric Learning)](#ML) - [Unsupervised Domain Adaptation](#UDA) - [Video Rescaling](#Video-Rescaling) - [Hand-Object Interaction](#Hand-Object-Interaction) - [Vision-and-Language Navigation](#VLN) - [数据集(Datasets)](#Datasets) - [其他(Others)](#Others) # Backbone **Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions** - Paper(Oral): https://arxiv.org/abs/2102.12122 - Code: https://github.com/whai362/PVT **AutoFormer: Searching Transformers for Visual Recognition** - Paper: https://arxiv.org/abs/2107.00651 - Code: https://github.com/microsoft/AutoML **Bias Loss for Mobile Neural Networks** - Paper: https://arxiv.org/abs/2107.11170 - Code: None **Vision Transformer with Progressive Sampling** - Paper: https://arxiv.org/abs/2108.01684 - Code: https://github.com/yuexy/PS-ViT **Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet** - Paper: https://arxiv.org/abs/2101.11986 - Code: https://github.com/yitu-opensource/T2T-ViT **Rethinking Spatial Dimensions of Vision Transformers** - Paper: https://arxiv.org/abs/2103.16302 - Code: https://github.com/naver-ai/pit **Swin Transformer: Hierarchical Vision Transformer using Shifted Windows** - Paper: https://arxiv.org/abs/2103.14030 - Code: https://github.com/microsoft/Swin-Transformer **Conformer: Local Features Coupling Global Representations for Visual Recognition** - Paper: https://arxiv.org/abs/2105.03889 - Code: https://github.com/pengzhiliang/Conformer **MicroNet: Improving Image Recognition with Extremely Low FLOPs** - Paper: https://arxiv.org/abs/2108.05894 - Code: https://github.com/liyunsheng13/micronet **Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition** - Paper: https://arxiv.org/abs/2102.01063 - Code: https://github.com/idstcv/ZenNAS # Visual Transformer **Swin Transformer: Hierarchical Vision Transformer using Shifted Windows** - Paper: https://arxiv.org/abs/2103.14030 - Code: https://github.com/microsoft/Swin-Transformer **An Empirical Study of Training Self-Supervised Vision Transformers** - Paper(Oral): https://arxiv.org/abs/2104.02057 - MoCo v3 Code: None **Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions** - Paper(Oral): https://arxiv.org/abs/2102.12122 - Code: https://github.com/whai362/PVT **Group-Free 3D Object Detection via Transformers** - Paper: https://arxiv.org/abs/2104.00678 - Code: None **Spatial-Temporal Transformer for Dynamic Scene Graph Generation** - Paper: https://arxiv.org/abs/2107.12309 - Code: None **Rethinking and Improving Relative Position Encoding for Vision Transformer** - Paper: https://arxiv.org/abs/2107.14222 - Code: https://github.com/microsoft/AutoML/tree/main/iRPE **Emerging Properties in Self-Supervised Vision Transformers** - Paper: https://arxiv.org/abs/2104.14294 - Code: https://github.com/facebookresearch/dino **Learning Spatio-Temporal Transformer for Visual Tracking** - Paper: https://arxiv.org/abs/2103.17154 - Code: https://github.com/researchmm/Stark **Fast Convergence of DETR with Spatially Modulated Co-Attention** - Paper: https://arxiv.org/abs/2101.07448 - Code: https://github.com/abc403/SMCA-replication **Vision Transformer with Progressive Sampling** - Paper: https://arxiv.org/abs/2108.01684 - Code: https://github.com/yuexy/PS-ViT **Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet** - Paper: https://arxiv.org/abs/2101.11986 - Code: https://github.com/yitu-opensource/T2T-ViT **Rethinking Spatial Dimensions of Vision Transformers** - Paper: https://arxiv.org/abs/2103.16302 - Code: https://github.com/naver-ai/pit **The Right to Talk: An Audio-Visual Transformer Approach** - Paper: https://arxiv.org/abs/2108.03256 - Code: None **Joint Inductive and Transductive Learning for Video Object Segmentation** - Paper: https://arxiv.org/abs/2108.03679 - Code: https://github.com/maoyunyao/JOINT **Conformer: Local Features Coupling Global Representations for Visual Recognition** - Paper: https://arxiv.org/abs/2105.03889 - Code: https://github.com/pengzhiliang/Conformer **Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformer** - Paper: https://arxiv.org/abs/2108.03032 - Code: https://github.com/zhiheLu/CWT-for-FSS **Paint Transformer: Feed Forward Neural Painting with Stroke Prediction** - Paper: https://arxiv.org/abs/2108.03798 - Code: https://github.com/wzmsltw/PaintTransformer **Conditional DETR for Fast Training Convergence** - Paper: https://arxiv.org/abs/2108.06152 - Code: https://github.com/Atten4Vis/ConditionalDETR **MUSIQ: Multi-scale Image Quality Transformer** - Paper: https://arxiv.org/abs/2108.05997 - Code: https://github.com/google-research/google-research/tree/master/musiq **SOTR: Segmenting Objects with Transformers** - Paper: https://arxiv.org/abs/2108.06747 - Code: https://github.com/easton-cau/SOTR **PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformers** - Paper(Oral): https://arxiv.org/abs/2108.08839 - Code: https://github.com/yuxumin/PoinTr **SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution with Skip-Transformer** - Paper: https://arxiv.org/abs/2108.04444 - Code: https://github.com/AllenXiangX/SnowflakeNet **Improving 3D Object Detection with Channel-wise Transformer** - Paper: https://arxiv.org/abs/2108.10723 - Code: https://github.com/hlsheng1/CT3D **TransFER: Learning Relation-aware Facial Expression Representations with Transformers** - Paper: https://arxiv.org/abs/2108.11116 - Code: None **GroupFormer: Group Activity Recognition with Clustered Spatial-Temporal Transformer** - Paper: https://arxiv.org/abs/2108.12630 - Code: https://github.com/xueyee/GroupFormer **Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category Reconstruction** - Paper: https://arxiv.org/abs/2109.00512 - Code: https://github.com/facebookresearch/co3d - Dataset: https://github.com/facebookresearch/co3d **Voxel Transformer for 3D Object Detection** - Paper: https://arxiv.org/abs/2109.02497 - Code: None **3D Human Texture Estimation from a Single Image with Transformers** - Homepage: https://www.mmlab-ntu.com/project/texformer/ - Paper(Oral): https://arxiv.org/abs/2109.02563 - Code: None **FuseFormer: Fusing Fine-Grained Information in Transformers for Video Inpainting** - Paper: https://arxiv.org/abs/2109.02974 - Code: https://github.com/ruiliu-ai/FuseFormer **CTRL-C: Camera calibration TRansformer with Line-Classification** - Paper: https://arxiv.org/abs/2109.02259 - Code: https://github.com/jwlee-vcl/CTRL-C **An End-to-End Transformer Model for 3D Object Detection** - Homepage: https://facebookresearch.github.io/3detr/ - Paper: https://arxiv.org/abs/2109.08141 - Code: https://github.com/facebookresearch/3detr **Eformer: Edge Enhancement based Transformer for Medical Image Denoising** - Paper: https://arxiv.org/abs/2109.08044 - Code: None **PnP-DETR: Towards Efficient Visual Analysis with Transformers** - Paper: https://arxiv.org/abs/2109.07036 - Code: https://github.com/twangnh/pnp-detr # 涨点神器 **FaPN: Feature-aligned Pyramid Network for Dense Image Prediction** - Paper: https://github.com/EMI-Group/FaPN - Code: https://arxiv.org/abs/2108.07058 **Unifying Nonlocal Blocks for Neural Networks** - Paper: https://arxiv.org/abs/2108.02451 - Code: https://github.com/zh460045050/SNL_ICCV2021 **Towards Learning Spatially Discriminative Feature Representations** - Paper: https://arxiv.org/abs/2109.01359 - Code: None # GAN **Labels4Free: Unsupervised Segmentation using StyleGAN** - Homepage: https://rameenabdal.github.io/Labels4Free/ - Paper: https://arxiv.org/abs/2103.14968 **GNeRF: GAN-based Neural Radiance Field without Posed Camera** - Paper(Oral): https://arxiv.org/abs/2103.15606 - Code: https://github.com/MQ66/gnerf **EigenGAN: Layer-Wise Eigen-Learning for GANs** - Paper: https://arxiv.org/abs/2104.12476 - Code: https://github.com/LynnHo/EigenGAN-Tensorflow **From Continuity to Editability: Inverting GANs with Consecutive Images** - Paper: https://arxiv.org/abs/2107.13812 - Code: https://github.com/Qingyang-Xu/InvertingGANs_with_ConsecutiveImgs **Sketch Your Own GAN** - Homepage: https://peterwang512.github.io/GANSketching/ - Paper: https://arxiv.org/abs/2108.02774 - 代码: https://github.com/peterwang512/GANSketching **Manifold Matching via Deep Metric Learning for Generative Modeling** - Paper: https://arxiv.org/abs/2106.10777 - Code: https://github.com/dzld00/pytorch-manifold-matching **Dual Projection Generative Adversarial Networks for Conditional Image Generation** - Paper: https://arxiv.org/abs/2108.09016 - Code: None **GAN Inversion for Out-of-Range Images with Geometric Transformations** - Paper: https://arxiv.org/abs/2108.08998 - Code: None **ReStyle: A Residual-Based StyleGAN Encoder via Iterative Refinement** - Homepage: https://yuval-alaluf.github.io/restyle-encoder/ - Paper: https://arxiv.org/abs/2104.02699 - Code: https://github.com/yuval-alaluf/restyle-encoder **StyleCLIP: Text-Driven Manipulation of StyleGAN Imagery** - Paper(Oral): https://arxiv.org/abs/2103.17249 - Code: https://github.com/orpatashnik/StyleCLIP **Image Synthesis via Semantic Composition** - Homepage: https://shepnerd.github.io/scg/ - Paper: https://arxiv.org/abs/2109.07053 - Code: https://github.com/dvlab-research/SCGAN # NAS **AutoFormer: Searching Transformers for Visual Recognition** - Paper: https://arxiv.org/abs/2107.00651 - Code: https://github.com/microsoft/AutoML **BN-NAS: Neural Architecture Search with Batch Normalization** - Paper: https://arxiv.org/abs/2108.07375 - Code: https://github.com/bychen515/BNNAS **Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition** - Paper: https://arxiv.org/abs/2102.01063 - Code: https://github.com/idstcv/ZenNAS # NeRF **GNeRF: GAN-based Neural Radiance Field without Posed Camera** - Paper(Oral): https://arxiv.org/abs/2103.15606 - Code: https://github.com/MQ66/gnerf **KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPs** - Paper: https://arxiv.org/abs/2103.13744 - Code: https://github.com/creiser/kilonerf **In-Place Scene Labelling and Understanding with Implicit Scene Representation** - Homepage: https://shuaifengzhi.com/Semantic-NeRF/ - Paper(Oral): https://arxiv.org/abs/2103.15875 **Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis** - Homepage: https://ajayj.com/dietnerf - Paper(DietNeRF): https://arxiv.org/abs/2104.00677 **BARF: Bundle-Adjusting Neural Radiance Fields** - Homepage: https://chenhsuanlin.bitbucket.io/bundle-adjusting-NeRF/ - Paper(Oral): https://arxiv.org/abs/2104.06405 - Code: https://github.com/chenhsuanlin/bundle-adjusting-NeRF **Self-Calibrating Neural Radiance Fields** - Paper: https://arxiv.org/abs/2108.13826 - Code: https://github.com/POSTECH-CVLab/SCNeRF **Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category Reconstruction** - Paper: https://arxiv.org/abs/2109.00512 - Code: https://github.com/facebookresearch/co3d - Dataset: https://github.com/facebookresearch/co3d **Neural Articulated Radiance Field** - Paper: https://arxiv.org/abs/2104.03110 - Code: https://github.com/nogu-atsu/NARF **NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo** - Paper(Oral): https://arxiv.org/abs/2109.01129 - Code: https://github.com/weiyithu/NerfingMVS # Loss **Rank & Sort Loss for Object Detection and Instance Segmentation** - Paper(Oral): https://arxiv.org/abs/2107.11669 - Code: https://github.com/kemaloksuz/RankSortLoss **Bias Loss for Mobile Neural Networks** - Paper: https://arxiv.org/abs/2107.11170 - Code: None **A Robust Loss for Point Cloud Registration** - Paper: https://arxiv.org/abs/2108.11682 - Code: None **Reconcile Prediction Consistency for Balanced Object Detection** - Paper: https://arxiv.org/abs/2108.10809 - Code: None # Zero-Shot Learning **FREE: Feature Refinement for Generalized Zero-Shot Learning** - Paper: https://arxiv.org/abs/2107.13807 - Code: https://github.com/shiming-chen/FREE **Discriminative Region-based Multi-Label Zero-Shot Learning** - Paper: https://arxiv.org/abs/2108.09301 - Code: https://arxiv.org/abs/2108.09301 # Few-Shot Learning **Relational Embedding for Few-Shot Classification** - Paper: https://arxiv.org/abs/2108.0966 - Code: https://github.com/dahyun-kang/renet **Few-Shot and Continual Learning with Attentive Independent Mechanisms** - Paper: https://arxiv.org/abs/2107.14053 - Code: https://github.com/huang50213/AIM-Fewshot-Continual # 长尾(Long-tailed) **Parametric Contrastive Learning** - Paper: https://arxiv.org/abs/2107.12028 - Code: https://github.com/jiequancui/Parametric-Contrastive-Learning # Vision and Language **VLGrammar: Grounded Grammar Induction of Vision and Language** - Paper: https://arxiv.org/abs/2103.12975 - Code: https://github.com/evelinehong/VLGrammar # 无监督/自监督(Un/Self-Supervised) **An Empirical Study of Training Self-Supervised Vision Transformers** - Paper(Oral): https://arxiv.org/abs/2104.02057 - MoCo v3 Code: None **DetCo: Unsupervised Contrastive Learning for Object Detection** - Paper: https://arxiv.org/abs/2102.04803 - Code: https://github.com/xieenze/DetCo **Enhancing Self-supervised Video Representation Learning via Multi-level Feature Optimization** - Paper: https://arxiv.org/abs/2108.02183 - Code: None **Improving Contrastive Learning by Visualizing Feature Transformation** - Paper(Oral): https://arxiv.org/abs/2108.02982 - Code: https://github.com/DTennant/CL-Visualizing-Feature-Transformation **Self-Supervised Visual Representations Learning by Contrastive Mask Prediction** - Paper: https://arxiv.org/abs/2108.08012 - Code: None **Temporal Knowledge Consistency for Unsupervised Visual Representation Learning** - Paper: https://arxiv.org/abs/2108.10668 - Code: None **MultiSiam: Self-supervised Multi-instance Siamese Representation Learning for Autonomous Driving** - Paper: https://arxiv.org/abs/2108.12178 - Code: https://github.com/KaiChen1998/MultiSiam **Spatio-temporal Self-Supervised Representation Learning for 3D Point Clouds** - Homepage: https://siyuanhuang.com/STRL/ - Paper: https://arxiv.org/abs/2109.00179 - Code: https://github.com/yichen928/STRL **Self-supervised Product Quantization for Deep Unsupervised Image Retrieval** - Paper: https://arxiv.org/abs/2109.02244 - Code: https://github.com/youngkyunJang/SPQ # Multi-Label Image Recognition(多标签图像识别) **Residual Attention: A Simple but Effective Method for Multi-Label Recognition** - Paper: https://arxiv.org/abs/2108.02456 - Code: https://github.com/Kevinz-code/CSRA # 2D目标检测(Object Detection) **DetCo: Unsupervised Contrastive Learning for Object Detection** - Paper: https://arxiv.org/abs/2102.04803 - Code: https://github.com/xieenze/DetCo **Detecting Invisible People** - Homepage: http://www.cs.cmu.edu/~tkhurana/invisible.htm - Code: https://arxiv.org/abs/2012.08419 **Active Learning for Deep Object Detection via Probabilistic Modeling** - Paper: https://arxiv.org/abs/2103.16130 - Code: None **Conditional Variational Capsule Network for Open Set Recognition** - Paper: https://arxiv.org/abs/2104.09159 - Code: https://github.com/guglielmocamporese/cvaecaposr **MDETR : Modulated Detection for End-to-End Multi-Modal Understanding** - Homepage: https://ashkamath.github.io/mdetr_page/ - Paper(Oral): https://arxiv.org/abs/2104.12763 - Code: https://github.com/ashkamath/mdetr **Rank & Sort Loss for Object Detection and Instance Segmentation** - Paper(Oral): https://arxiv.org/abs/2107.11669 - Code: https://github.com/kemaloksuz/RankSortLoss **SimROD: A Simple Adaptation Method for Robust Object Detection** - Paper(Oral): https://arxiv.org/abs/2107.13389 - Code: None **GraphFPN: Graph Feature Pyramid Network for Object Detection** - Paper: https://arxiv.org/abs/2108.00580 - Code: None **Fast Convergence of DETR with Spatially Modulated Co-Attention** - Paper: https://arxiv.org/abs/2101.07448 - Code: https://github.com/abc403/SMCA-replication **Conditional DETR for Fast Training Convergence** - Paper: https://arxiv.org/abs/2108.06152 - Code: https://github.com/Atten4Vis/ConditionalDETR **TOOD: Task-aligned One-stage Object Detection** - Paper(Oral): https://arxiv.org/abs/2108.07755 - Code: https://github.com/fcjian/TOOD **Reconcile Prediction Consistency for Balanced Object Detection** - Paper: https://arxiv.org/abs/2108.10809 - Code: None **Mutual Supervision for Dense Object Detection** - Paper: https://arxiv.org/abs/2109.05986 - Code: https://github.com/MCG-NJU/MuSu-Detection **PnP-DETR: Towards Efficient Visual Analysis with Transformers** - Paper: https://arxiv.org/abs/2109.07036 - Code: https://github.com/twangnh/pnp-detr ## 半监督目标检测 **End-to-End Semi-Supervised Object Detection with Soft Teacher** - Paper: https://arxiv.org/abs/2106.09018 - Code: None ## 旋转目标检测 **Oriented R-CNN for Object Detection** - Paper: https://arxiv.org/abs/2108.05699 - Code: https://github.com/jbwang1997/OBBDetection ## Few-Shot目标检测 **DeFRCN: Decoupled Faster R-CNN for Few-Shot Object Detection** - Paper: https://arxiv.org/abs/2108.09017 - Code: https://github.com/er-muyue/DeFRCN ## 语义分割(Semantic Segmentation) **Personalized Image Semantic Segmentation** - Paper: https://arxiv.org/abs/2107.13978 - Code: https://github.com/zhangyuygss/PIS - Dataset: https://github.com/zhangyuygss/PIS **Standardized Max Logits: A Simple yet Effective Approach for Identifying Unexpected Road Obstacles in Urban-Scene Segmentation** - Paper(Oral): https://arxiv.org/abs/2107.11264 - Code: None **Enhanced Boundary Learning for Glass-like Object Segmentation** - Paper: https://arxiv.org/abs/2103.15734 - Code: https://github.com/hehao13/EBLNet **Self-Regulation for Semantic Segmentation** - Paper: https://arxiv.org/abs/2108.09702 - Code: https://github.com/dongzhang89/SR-SS **Mining Contextual Information Beyond Image for Semantic Segmentation** - Paper: https://arxiv.org/abs/2108.11819 - Code: https://github.com/CharlesPikachu/mcibi **Standardized Max Logits: A Simple yet Effective Approach for Identifying Unexpected Road Obstacles in Urban-Scene Segmentation** - Paper: https://arxiv.org/abs/2107.11264 - Code: https://github.com/shjung13/Standardized-max-logits **ISNet: Integrate Image-Level and Semantic-Level Context for Semantic Segmentation** - Paper: https://arxiv.org/abs/2108.12382 - Code: https://github.com/SegmentationBLWX/sssegmentation ## 无监督域自适应语义分割(Unsupervised Domain Ddaption Semantic Segmentation) **Multi-Anchor Active Domain Adaptation for Semantic Segmentation** - Paper(Oral): https://arxiv.org/abs/2108.08012 - Code: https://github.com/munanning/MADA 论文下载链接：https://arxiv.org/abs/2108.08012 ## Few-Shot语义分割 **Learning Meta-class Memory for Few-Shot Semantic Segmentation** - Paper: https://arxiv.org/abs/2108.02958' - Code: None **Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformer** - Paper: https://arxiv.org/abs/2108.03032 - Code: https://github.com/zhiheLu/CWT-for-FSS ## 半监督语义分割(Semi-supervised Semantic Segmentation) **Leveraging Auxiliary Tasks with Affinity Learning for Weakly Supervised Semantic Segmentation** - Paper: https://arxiv.org/abs/2107.11787 - Code: None **Re-distributing Biased Pseudo Labels for Semi-supervised Semantic Segmentation: A Baseline Investigation** - Paper(Oral): https://arxiv.org/abs/2107.11279 - Code: https://github.com/CVMI-Lab/DARS **Pixel Contrastive-Consistent Semi-Supervised Semantic Segmentation** - Paper: https://arxiv.org/abs/2108.09025 - Code: None ## 弱监督语义分割(Weakly Supervised Semantic Segmentation) **Complementary Patch for Weakly Supervised Semantic Segmentation** - Paper: https://arxiv.org/abs/2108.03852 - Code: None ## 无监督分割(Unsupervised Segmentation) **Labels4Free: Unsupervised Segmentation using StyleGAN** - Homepage: https://rameenabdal.github.io/Labels4Free/ - Paper: https://arxiv.org/abs/2103.14968 # 实例分割(Instance Segmentation) **Instances as Queries** - Paper: https://arxiv.org/abs/2105.01928 - Code: https://github.com/hustvl/QueryInst **Crossover Learning for Fast Online Video Instance Segmentation** - Paper: https://arxiv.org/abs/2104.05970 - Code: https://github.com/hustvl/CrossVIS **Rank & Sort Loss for Object Detection and Instance Segmentation** - Paper(Oral): https://arxiv.org/abs/2107.11669 - Code: https://github.com/kemaloksuz/RankSortLoss **SOTR: Segmenting Objects with Transformers** - Paper: https://arxiv.org/abs/2108.06747 - Code: https://github.com/easton-cau/SOTR # 医学图像分割(Medical Image Segmentation) **Recurrent Mask Refinement for Few-Shot Medical Image Segmentation** - Paper: https://arxiv.org/abs/2108.00622 - Code: https://github.com/uci-cbcl/RP-Net # 视频目标分割(Video Object Segmentation) **Full-Duplex Strategy for Video Object Segmentation** - Homepage: http://dpfan.net/FSNet/ - Paper: https://arxiv.org/abs/2108.03151 - Code: https://github.com/GewelsJI/FSNet **Joint Inductive and Transductive Learning for Video Object Segmentation** - Paper: https://arxiv.org/abs/2108.03679 - Code: https://github.com/maoyunyao/JOINT # Few-shot Segmentation **Mining Latent Classes for Few-shot Segmentation** - Paper(Oral): https://arxiv.org/abs/2103.15402 - Code: https://github.com/LiheYoung/MiningFSS # 人体运动分割(Human Motion Segmentation) **Graph Constrained Data Representation Learning for Human Motion Segmentation** - Paper: https://arxiv.org/abs/2107.13362 - Code: None # 目标跟踪(Object Tracking) **Learning to Track Objects from Unlabeled Videos** - Paper: https://arxiv.org/abs/2108.12711 - Code: https://github.com/VISION-SJTU/USOT **Learning Spatio-Temporal Transformer for Visual Tracking** - Paper: https://arxiv.org/abs/2103.17154 - Code: https://github.com/researchmm/Stark **Learning to Adversarially Blur Visual Object Tracking** - Paper: https://arxiv.org/abs/2107.12085 - Code: https://github.com/tsingqguo/ABA **HiFT: Hierarchical Feature Transformer for Aerial Tracking** - Paper: https://arxiv.org/abs/2108.00202 - Code: https://github.com/vision4robotics/HiFT **Learn to Match: Automatic Matching Network Design for Visual Tracking** - Paper: https://arxiv.org/abs/2108.00803 - Code: https://github.com/JudasDie/SOTS **Saliency-Associated Object Tracking** - Paper: https://arxiv.org/abs/2108.03637 - Code: https://github.com/ZikunZhou/SAOT.git ## RGBD 目标跟踪 **DepthTrack: Unveiling the Power of RGBD Tracking** - Paper: https://arxiv.org/abs/2108.13962 - Code: https://github.com/xiaozai/DeT - Dataset: https://github.com/xiaozai/DeT # 3D Point Cloud **Spatio-temporal Self-Supervised Representation Learning for 3D Point Clouds** - Homepage: https://siyuanhuang.com/STRL/ - Paper: https://arxiv.org/abs/2109.00179 - Code: https://github.com/yichen928/STRL **Unsupervised Point Cloud Pre-Training via View-Point Occlusion, Completion** - Homepage: https://hansen7.github.io/OcCo/ - Paper: https://arxiv.org/abs/2010.01089 - Code: https://github.com/hansen7/OcCo **DRINet: A Dual-Representation Iterative Learning Network for Point Cloud Segmentation** - Paper: https://arxiv.org/abs/2108.04023 - Code: None **Adaptive Graph Convolution for Point Cloud Analysis** - Paper: https://arxiv.org/abs/2108.08035 - Code: https://github.com/hrzhou2/AdaptConv-master **Unsupervised Point Cloud Pre-Training via View-Point Occlusion, Completion** - Paper: https://arxiv.org/abs/2010.01089 - Code: https://github.com/hansen7/OcCo # 3D Object Detection(3D目标检测) **Group-Free 3D Object Detection via Transformers** - Paper: https://arxiv.org/abs/2104.00678 - Code: None **Improving 3D Object Detection with Channel-wise Transformer** - Paper: https://arxiv.org/abs/2108.10723 - Code: https://github.com/hlsheng1/CT3D **AutoShape: Real-Time Shape-Aware Monocular 3D Object Detection** - Paper: https://arxiv.org/abs/2108.11127 - Code: https://github.com/zongdai/AutoShape **4D-Net for Learned Multi-Modal Alignment** - Paper: https://arxiv.org/abs/2109.01066 - Code: None **Voxel Transformer for 3D Object Detection** - Paper: https://arxiv.org/abs/2109.02497 - Code: None **Pyramid R-CNN: Towards Better Performance and Adaptability for 3D Object Detection** - Paper: https://arxiv.org/abs/2109.02499 - Code: None **An End-to-End Transformer Model for 3D Object Detection** - Homepage: https://facebookresearch.github.io/3detr/ - Paper: https://arxiv.org/abs/2109.08141 - Code: https://github.com/facebookresearch/3detr ## 3D Semantic Segmentation(3D语义分割) **ReDAL: Region-based and Diversity-aware Active Learning for Point Cloud Semantic Segmentation** - Paper: https://arxiv.org/abs/2107.11769 - Code: None **Learning with Noisy Labels for Robust Point Cloud Segmentation** - Homepage: https://shuquanye.com/PNAL_website/ - Paper(Oral): https://arxiv.org/abs/2107.14230 **VMNet: Voxel-Mesh Network for Geodesic-Aware 3D Semantic Segmentation** - Paper(Oral): https://arxiv.org/abs/2107.13824 - Code: https://github.com/hzykent/VMNet **Sparse-to-dense Feature Matching: Intra and Inter domain Cross-modal Learning in Domain Adaptation for 3D Semantic Segmentation** - Paper: https://arxiv.org/abs/2107.14724 - Code: https://github.com/leolyj/DsCML **DRINet: A Dual-Representation Iterative Learning Network for Point Cloud Segmentation** - Paper: https://arxiv.org/abs/2108.04023 - Code: None **Adaptive Graph Convolution for Point Cloud Analysis** - Paper: https://arxiv.org/abs/2108.08035 - Code: https://github.com/hrzhou2/AdaptConv-master ## 3D Instance Segmentation(3D实例分割) **Hierarchical Aggregation for 3D Instance Segmentation** - Paper: https://arxiv.org/abs/2108.02350 - Code: https://github.com/hustvl/HAIS ## 3D Multi-Object Tracking(3D多目标跟踪) **Exploring Simple 3D Multi-Object Tracking for Autonomous Driving** - Paper: https://arxiv.org/abs/2108.10312 - Code: https://github.com/qcraftai/simtrack ## Point Cloud Denoising(点云去噪) **Score-Based Point Cloud Denoising** - Paper: https://arxiv.org/abs/2107.10981 - Code: None ## Point Cloud Registration(点云配准) **HRegNet: A Hierarchical Network for Large-scale Outdoor LiDAR Point Cloud Registration** - Homepage: https://ispc-group.github.io/hregnet - Paper: https://arxiv.org/abs/2107.11992 - Code: https://github.com/ispc-lab/HRegNet **A Robust Loss for Point Cloud Registration** - Paper: https://arxiv.org/abs/2108.11682 - Code: None # Point Cloud Completion(点云补全) **PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformers** - Paper(Oral): https://arxiv.org/abs/2108.08839 - Code: https://github.com/yuxumin/PoinTr **SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution with Skip-Transformer** - Paper: https://arxiv.org/abs/2108.04444 - Code: https://github.com/AllenXiangX/SnowflakeNet # 雷达语义分割(Radar Semantic Segmentation) **Multi-View Radar Semantic Segmentation** - Paper: https://arxiv.org/abs/2103.16214 - Code: https://github.com/valeoai/MVRSS # 图像恢复(Image Restoration) **Dynamic Attentive Graph Learning for Image Restoration** - Paper: https://arxiv.org/abs/2109.06620 - Code: https://github.com/jianzhangcs/DAGL # 超分辨率(Super-Resolution) **Learning for Scale-Arbitrary Super-Resolution from Scale-Specific Networks** - Paper: https://arxiv.org/abs/2004.03791 - Code: https://github.com/LongguangWang/ArbSR **Mutual Affine Network for Spatially Variant Kernel Estimation in Blind Image Super-Resolution** - Paper: https://arxiv.org/abs/2108.05302 - Code: https://github.com/JingyunLiang/MANet **Deep Reparametrization of Multi-Frame Super-Resolution and Denoising** - Paper(Oral): https://arxiv.org/abs/2108.08286 - Code: None **Dual-Camera Super-Resolution with Aligned Attention Modules** - Homepage: https://tengfei-wang.github.io/Dual-Camera-SR/index.html - Paper: https://arxiv.org/abs/2109.01349 - Code: https://github.com/Tengfei-Wang/DualCameraSR - Dataset: https://tengfei-wang.github.io/Dual-Camera-SR/index.html **Real-world Video Super-resolution: A Benchmark Dataset and A Decomposition based Learning Scheme** - Paper: https://www4.comp.polyu.edu.hk/~cslzhang/paper/ICCV21_RealVSR.pdf - Code: https://github.com/IanYeung/RealVSR - Dataset: https://github.com/IanYeung/RealVSR # 去噪(Denoising) **Deep Reparametrization of Multi-Frame Super-Resolution and Denoising** - Paper(Oral): https://arxiv.org/abs/2108.08286 - Code: None **Rethinking Deep Image Prior for Denoising** - Paper: https://arxiv.org/abs/2108.12841 - Code: https://github.com/gistvision/DIP-denosing # 医学图像去噪(Medical Image Denoising) **Eformer: Edge Enhancement based Transformer for Medical Image Denoising** - Paper: https://arxiv.org/abs/2109.08044 - Code: None # 去模糊(Deblurring) **Rethinking Coarse-to-Fine Approach in Single Image Deblurring** - Paper: https://arxiv.org/abs/2108.05054 - Code: https://github.com/chosj95/MIMO-UNet **Single Image Defocus Deblurring Using Kernel-Sharing Parallel Atrous Convolutions** - Paper: https://arxiv.org/abs/2108.09108 - Code: None # 阴影去除(Shadow Removal) **CANet: A Context-Aware Network for Shadow Removal** - Paper: https://arxiv.org/abs/2108.09894 - Code: https://github.com/Zipei-Chen/CANet # 视频插帧(Video Frame Interpolation) **XVFI: eXtreme Video Frame Interpolation** - Paper(Oral): https://arxiv.org/abs/2103.16206 - Code: https://github.com/JihyongOh/XVFI - Dataset: https://github.com/JihyongOh/XVFI **Asymmetric Bilateral Motion Estimation for Video Frame Interpolation** - Paper: https://arxiv.org/abs/2108.06815 - Code: https://github.com/JunHeum/ABME # 视频修复/补全(Video Inpainting) **FuseFormer: Fusing Fine-Grained Information in Transformers for Video Inpainting** - Paper: https://arxiv.org/abs/2109.02974 - Code: https://github.com/ruiliu-ai/FuseFormer # 行人重识别(Person Re-identification) **TransReID: Transformer-based Object Re-Identification** - Paper: https://arxiv.org/abs/2102.04378 - Code: https://github.com/heshuting555/TransReID **IDM: An Intermediate Domain Module for Domain Adaptive Person Re-ID** - Paper(Oral): https://arxiv.org/abs/2108.02413 - Code: https://github.com/SikaStar/IDM # 行人搜索(Person Search) **Weakly Supervised Person Search with Region Siamese Networks** - Paper: https://arxiv.org/abs/2109.06109 - Code: None # 2D/3D人体姿态估计(2D/3D Human Pose Estimation) ## 2D 人体姿态估计 **Human Pose Regression with Residual Log-likelihood Estimation** - Paper(Oral): https://arxiv.org/abs/2107.11291 - Code(RLE): https://github.com/Jeff-sjtu/res-loglikelihood-regression **Online Knowledge Distillation for Efficient Pose Estimation** - Paper: https://arxiv.org/abs/2108.02092 - Code: None ## 3D 人体姿态估计 **Probabilistic Monocular 3D Human Pose Estimation with Normalizing Flows** - Paper: https://arxiv.org/abs/2107.13788 - Code: https://github.com/twehrbein/Probabilistic-Monocular-3D-Human-Pose-Estimation-with-Normalizing-Flows **Graph-Based 3D Multi-Person Pose Estimation Using Multi-View Images** - Paper: https://arxiv.org/abs/2109.05885 - Code: None # 3D人头重建(3D Head Reconstruction) **H3D-Net: Few-Shot High-Fidelity 3D Head Reconstruction** - Homepage: https://crisalixsa.github.io/h3d-net/ - Paper: https://arxiv.org/abs/2107.12512 # 人脸识别(Face Recognition) **SynFace: Face Recognition with Synthetic Data** - Paper: https://arxiv.org/abs/2108.07960 - Code: None # Facial Expression Recognition(人脸表情识别) **TransFER: Learning Relation-aware Facial Expression Representations with Transformers** - Paper: https://arxiv.org/abs/2108.11116 - Code: None # 行为识别(Action Recognition) **MGSampler: An Explainable Sampling Strategy for Video Action Recognition** - Paper: https://arxiv.org/abs/2104.09952 - Code: None **Channel-wise Topology Refinement Graph Convolution for Skeleton-Based Action Recognition** - Paper: https://arxiv.org/abs/2107.12213 - Code: https://github.com/Uason-Chen/CTR-GCN **Enhancing Self-supervised Video Representation Learning via Multi-level Feature Optimization** - Paper: https://arxiv.org/abs/2108.02183 - Code: None **Dynamic Network Quantization for Efficient Video Inference** - Homepage: https://cs-people.bu.edu/sunxm/VideoIQ/project.html - Paper: https://arxiv.org/abs/2108.10394 - Code: https://github.com/sunxm2357/VideoIQ # 时序动作定位(Temporal Action Localization) **Enriching Local and Global Contexts for Temporal Action Localization** - Paper: https://arxiv.org/abs/2107.12960 - Code: None # 动作检测(Action Detection) **Class Semantics-based Attention for Action Detection** - Paper: https://arxiv.org/abs/2109.02613 - Code: None # 群体活动识别(Group Activity Recognition) **GroupFormer: Group Activity Recognition with Clustered Spatial-Temporal Transformer** - Paper: https://arxiv.org/abs/2108.12630 - Code: https://github.com/xueyee/GroupFormer # 手语识别(Sign Language Recognition) **Visual Alignment Constraint for Continuous Sign Language Recognition** - Paper: https://arxiv.org/abs/2104.02330 - Code: https://github.com/ycmin95/VAC_CSLR # 文本检测(Text Detection) **Adaptive Boundary Proposal Network for Arbitrary Shape Text Detection** - Paper: https://arxiv.org/abs/2107.12664 - Code: https://github.com/GXYM/TextBPN # 文本识别(Text Recognition) **Joint Visual Semantic Reasoning: Multi-Stage Decoder for Text Recognition** - Paper: https://arxiv.org/abs/2107.12090 - Code: None # 文本替换(Text Replacement) **STRIVE: Scene Text Replacement In Videos** - Homepage: https://striveiccv2021.github.io/STRIVE-ICCV2021/ - Paper: https://arxiv.org/abs/2109.02762 - Code: https://github.com/striveiccv2021/STRIVE-ICCV2021/ - Datasets: https://github.com/striveiccv2021/STRIVE-ICCV2021/ # 视觉问答(Visual Question Answering, VQA) **Greedy Gradient Ensemble for Robust Visual Question Answering** - Paper: https://arxiv.org/abs/2107.12651 - Code: https://github.com/GeraldHan/GGE # 对抗攻击(Adversarial Attack) **Feature Importance-aware Transferable Adversarial Attacks** - Paper: https://arxiv.org/abs/2107.14185 - Code: https://github.com/hcguoO0/FIA **AdvDrop: Adversarial Attack to DNNs by Dropping Information** - Paper: https://arxiv.org/abs/2108.09034 - Code: https://github.com/RjDuan/AdvDrop # 深度估计(Depth Estimation) **NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo** - Paper(Oral): https://arxiv.org/abs/2109.01129 - Code: https://github.com/weiyithu/NerfingMVS ## 单目深度估计 **MonoIndoor: Towards Good Practice of Self-Supervised Monocular Depth Estimation for Indoor Environments** - Paper: https://arxiv.org/abs/2107.12429 - Code: None **Towards Interpretable Deep Networks for Monocular Depth Estimation** - Paper: https://arxiv.org/abs/2108.05312 - Code: https://github.com/youzunzhi/InterpretableMDE **Regularizing Nighttime Weirdness: Efficient Self-supervised Monocular Depth Estimation in the Dark** - Paper: https://arxiv.org/abs/2108.03830 - Code: https://github.com/w2kun/RNW **Self-supervised Monocular Depth Estimation for All Day Images using Domain Separation** - Paper: https://arxiv.org/abs/2108.07628 - Code: https://github.com/LINA-lln/ADDS-DepthNet **StructDepth: Leveraging the structural regularities for self-supervised indoor depth estimation** - Paper: https://arxiv.org/abs/2108.08574 - Code: https://github.com/SJTU-ViSYS/StructDepth # 视线估计(Gaze Estimation) **Generalizing Gaze Estimation with Outlier-guided Collaborative Adaptation** - Paper: https://arxiv.org/abs/2107.13780 - Code: https://github.com/DreamtaleCore/PnP-GA # 人群计数(Crowd Counting) **Rethinking Counting and Localization in Crowds:A Purely Point-Based Framework** - Paper(Oral): https://arxiv.org/abs/2107.12746 - Code(P2PNet): https://github.com/TencentYoutuResearch/CrowdCounting-P2PNet **Uniformity in Heterogeneity:Diving Deep into Count Interval Partition for Crowd Counting** - Paper: https://arxiv.org/abs/2107.12619 - Code: https://github.com/TencentYoutuResearch/CrowdCounting-UEPNet # 车道线检测(Lane-Detection) **VIL-100: A New Dataset and A Baseline Model for Video Instance Lane Detection** - Paper: https://arxiv.org/abs/2108.08482 - Code: https://github.com/yujun0-0/MMA-Net - Dataset: https://github.com/yujun0-0/MMA-Net # 轨迹预测(Trajectory Prediction) **Human Trajectory Prediction via Counterfactual Analysis** - Paper: https://arxiv.org/abs/2107.14202 - Code: https://github.com/CHENGY12/CausalHTP **Personalized Trajectory Prediction via Distribution Discrimination** - Paper: https://arxiv.org/abs/2107.14204 - Code: https://github.com/CHENGY12/DisDis **MG-GAN: A Multi-Generator Model Preventing Out-of-Distribution Samples in Pedestrian Trajectory Prediction** - Paper: https://arxiv.org/abs/2108.09274 - Code: https://github.com/selflein/MG-GAN **Social NCE: Contrastive Learning of Socially-aware Motion Representations** - Paper: https://arxiv.org/abs/2012.11717 - Code: https://github.com/vita-epfl/social-nce **Safety-aware Motion Prediction with Unseen Vehicles for Autonomous Driving** - Paper: https://arxiv.org/abs/2109.01510 - Code: https://github.com/xrenaa/Safety-Aware-Motion-Prediction # 异常检测(Anomaly Detection) **Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning** - Paper: https://arxiv.org/abs/2101.10030 - Code: https://github.com/tianyu0207/RTFM # 场景图生成(Scene Graph Generation) **Spatial-Temporal Transformer for Dynamic Scene Graph Generation** - Paper: https://arxiv.org/abs/2107.12309 - Code: None # 图像编辑(Image Editing) **Sketch Your Own GAN** - Homepage: https://peterwang512.github.io/GANSketching/ - Paper: https://arxiv.org/abs/2108.02774 - 代码: https://github.com/peterwang512/GANSketching # 图像合成(Image Synthesis) **Image Synthesis via Semantic Composition** - Homepage: https://shepnerd.github.io/scg/ - Paper: https://arxiv.org/abs/2109.07053 - Code: https://github.com/dvlab-research/SCGAN # 图像检索(Image Retrieval) **Self-supervised Product Quantization for Deep Unsupervised Image Retrieval** - Paper: https://arxiv.org/abs/2109.02244 - Code: https://github.com/youngkyunJang/SPQ # 三维重建(3D Reconstruction) **Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category Reconstruction** - Paper: https://arxiv.org/abs/2109.00512 - Code: https://github.com/facebookresearch/co3d - Dataset: https://github.com/facebookresearch/co3d # 视频稳像(Video Stabilization) **Out-of-boundary View Synthesis Towards Full-Frame Video Stabilization** - Paper: https://arxiv.org/abs/2108.09041 - 代码：https://github.com/Annbless/OVS_Stabilization # 细粒度识别(Fine-Grained Recognition) **Webly Supervised Fine-Grained Recognition: Benchmark Datasets and An Approach** - Paper: https://arxiv.org/abs/2108.02399 - Code: https://github.com/NUST-Machine-Intelligence-Laboratory/weblyFG-dataset - Dataset: https://github.com/NUST-Machine-Intelligence-Laboratory/weblyFG-dataset # 风格迁移(Style Transfer) **AdaAttN: Revisit Attention Mechanism in Arbitrary Neural Style Transfer** - Paper: https://arxiv.org/abs/2108.03647 - Paddle Code：https://github.com/PaddlePaddle/PaddleGAN - PyTorch Code：https://github.com/Huage001/AdaAttN # 神经绘画(Neural Painting) **Paint Transformer: Feed Forward Neural Painting with Stroke Prediction** - Paper: https://arxiv.org/abs/2108.03798 - Code: https://github.com/wzmsltw/PaintTransformer # 特征匹配(Feature Matching) **Learning to Match Features with Seeded Graph Matching Network** - Paper: https://arxiv.org/abs/2108.08771 - Code: https://github.com/vdvchen/SGMNet # 语义对应(Semantic Correspondence) **Multi-scale Matching Networks for Semantic Correspondence** - Paper: https://arxiv.org/abs/2108.00211 - Code: https://github.com/wintersun661/MMNet # 边缘检测(Edge Detection) **Pixel Difference Networks for Efficient Edge Detection** - Paper: https://arxiv.org/abs/2108.07009 - Code: https://github.com/zhuoinoulu/pidinet **RINDNet: Edge Detection for Discontinuity in Reflectance, Illumination, Normal and Depth** - Paper: https://arxiv.org/abs/2108.00616 - Code : https://github.com/MengyangPu/RINDNet - Dataset: https://github.com/MengyangPu/RINDNet # 相机标定(Camera calibration) **CTRL-C: Camera calibration TRansformer with Line-Classification** - Paper: https://arxiv.org/abs/2109.02259 - Code: https://github.com/jwlee-vcl/CTRL-C # 图像质量评估(Image Quality Assessment) **MUSIQ: Multi-scale Image Quality Transformer** - Paper: https://arxiv.org/abs/2108.05997 - Code: https://github.com/google-research/google-research/tree/master/musiq # 度量学习(Metric Learning) **Deep Relational Metric Learning** - Paper: https://arxiv.org/abs/2108.10026 - Code: https://github.com/zbr17/DRML **Towards Interpretable Deep Metric Learning with Structural Matching** - Paper: https://arxiv.org/abs/2108.05889 - Code: https://github.com/wl-zhao/DIML # Unsupervised Domain Adaptation **Recursively Conditional Gaussian for Ordinal Unsupervised Domain Adaptation** - Paper(Oral): https://arxiv.org/abs/2107.13467 - Code: None # Video Rescaling **Self-Conditioned Probabilistic Learning of Video Rescaling** - Paper: https://arxiv.org/abs/2107.11639 - Code: None # Hand-Object Interaction **Learning a Contact Potential Field to Model the Hand-Object Interaction** - Paper: https://arxiv.org/abs/2012.00924 - Code: https://lixiny.github.io/CPF # Vision-and-Language Navigation **Airbert: In-domain Pretraining for Vision-and-Language Navigation** - Paper: https://arxiv.org/abs/2108.09105 - Code: https://airbert-vln.github.io/ - Dataset: https://airbert-vln.github.io/ # 数据集(Datasets) **RINDNet: Edge Detection for Discontinuity in Reflectance, Illumination, Normal and Depth** - Paper: https://arxiv.org/abs/2108.00616 - Code : https://github.com/MengyangPu/RINDNet - Dataset: https://github.com/MengyangPu/RINDNet **Panoptic Narrative Grounding** - Homepage: https://bcv-uniandes.github.io/panoptic-narrative-grounding/ - Paper(Oral): https://arxiv.org/abs/2109.04988 - Code: https://github.com/BCV-Uniandes/PNG - Dataset: https://github.com/BCV-Uniandes/PNG **STRIVE: Scene Text Replacement In Videos** - Homepage: https://striveiccv2021.github.io/STRIVE-ICCV2021/ - Paper: https://arxiv.org/abs/2109.02762 - Code: https://github.com/striveiccv2021/STRIVE-ICCV2021/ - Datasets: https://github.com/striveiccv2021/STRIVE-ICCV2021/ **Real-world Video Super-resolution: A Benchmark Dataset and A Decomposition based Learning Scheme** - Paper: https://www4.comp.polyu.edu.hk/~cslzhang/paper/ICCV21_RealVSR.pdf - Code: https://github.com/IanYeung/RealVSR - Dataset: https://github.com/IanYeung/RealVSR **Matching in the Dark: A Dataset for Matching Image Pairs of Low-light Scenes** - Paper: https://arxiv.org/abs/2109.03585 - Code: None **Dual-Camera Super-Resolution with Aligned Attention Modules** - Homepage: https://tengfei-wang.github.io/Dual-Camera-SR/index.html - Paper: https://arxiv.org/abs/2109.01349 - Code: https://github.com/Tengfei-Wang/DualCameraSR - Dataset: https://tengfei-wang.github.io/Dual-Camera-SR/index.html **DepthTrack: Unveiling the Power of RGBD Tracking** - Paper: https://arxiv.org/abs/2108.13962 - Code: https://github.com/xiaozai/DeT - Dataset: https://github.com/xiaozai/DeT **Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category Reconstruction** - Paper: https://arxiv.org/abs/2109.00512 - Code: https://github.com/facebookresearch/co3d - Dataset: https://github.com/facebookresearch/co3d **BioFors: A Large Biomedical Image Forensics Dataset** - Paper: https://arxiv.org/abs/2108.12961 - Code: None - Dataset: None **Webly Supervised Fine-Grained Recognition: Benchmark Datasets and An Approach** - Paper: https://arxiv.org/abs/2108.02399 - Code: https://github.com/NUST-Machine-Intelligence-Laboratory/weblyFG-dataset - Dataset: https://github.com/NUST-Machine-Intelligence-Laboratory/weblyFG-dataset **Airbert: In-domain Pretraining for Vision-and-Language Navigation** - Paper: https://arxiv.org/abs/2108.09105 - Code: https://airbert-vln.github.io/ - Dataset: https://airbert-vln.github.io/ **Overfitting the Data: Compact Neural Video Delivery via Content-aware Feature Modulation** - Paper: http://arxiv.org/abs/2108.08202 - Code: https://github.com/Neural-video-delivery/CaFM-Pytorch-ICCV2021 - Dataset: https://github.com/Neural-video-delivery/CaFM-Pytorch-ICCV2021 **VIL-100: A New Dataset and A Baseline Model for Video Instance Lane Detection** - Paper: https://arxiv.org/abs/2108.08482 - Code: https://github.com/yujun0-0/MMA-Net - Dataset: https://github.com/yujun0-0/MMA-Net **XVFI: eXtreme Video Frame Interpolation** - Paper(Oral): https://arxiv.org/abs/2103.16206 - Code: https://github.com/JihyongOh/XVFI - Dataset: https://github.com/JihyongOh/XVFI **Personalized Image Semantic Segmentation** - Paper: https://arxiv.org/abs/2107.13978 - Code: https://github.com/zhangyuygss/PIS - Dataset: https://github.com/zhangyuygss/PIS **H3D-Net: Few-Shot High-Fidelity 3D Head Reconstruction** - Homepage: https://crisalixsa.github.io/h3d-net/ - Paper: https://arxiv.org/abs/2107.12512 # 其他(Others) **Panoptic Narrative Grounding** - Homepage: https://bcv-uniandes.github.io/panoptic-narrative-grounding/ - Paper(Oral): https://arxiv.org/abs/2109.04988 - Code: https://github.com/BCV-Uniandes/PNG - Dataset: https://github.com/BCV-Uniandes/PNG **NEAT: Neural Attention Fields for End-to-End Autonomous Driving** - Paper: https://arxiv.org/abs/2109.04456 - https://github.com/autonomousvision/neat **Keep CALM and Improve Visual Feature Attribution** - Paper: https://arxiv.org/abs/2106.07861 - Code: https://github.com/naver-ai/calm **YouRefIt: Embodied Reference Understanding with Language and Gesture** - Paper: https://arxiv.org/abs/2109.03413 - Code: None **Pri3D: Can 3D Priors Help 2D Representation Learning?** - Paper: https://arxiv.org/abs/2104.11225 - Code: https://github.com/Sekunde/Pri3D **Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neural Networks in Frequency Domain** - Paper: https://arxiv.org/abs/2108.08487 - Code: https://github.com/iCGY96/APR **Continual Learning for Image-Based Camera Localization** - Paper: https://arxiv.org/abs/2108.09112 - Code: None **Multi-Task Self-Training for Learning General Representations** - Paper: https://arxiv.org/abs/2108.11353 - Code: None **A Unified Objective for Novel Class Discovery** - Homepage: https://ncd-uno.github.io/ - Paper(Oral): https://arxiv.org/abs/2108.08536 - Code: https://github.com/DonkeyShot21/UNO **Global Pooling, More than Meets the Eye: Position Information is Encoded Channel-Wise in CNNs** - Paper: https://arxiv.org/abs/2108.07884 - Code: https://github.com/islamamirul/PermuteNet **Overfitting the Data: Compact Neural Video Delivery via Content-aware Feature Modulation** - Paper: http://arxiv.org/abs/2108.08202 - Code: https://github.com/Neural-video-delivery/CaFM-Pytorch-ICCV2021 - Dataset: https://github.com/Neural-video-delivery/CaFM-Pytorch-ICCV2021 **Impact of Aliasing on Generalizatin in Deep Convolutional Networks** - Paper: https://arxiv.org/abs/2108.03489 - Code: None **Out-of-Core Surface Reconstruction via Global TGV Minimization** - Paper: https://arxiv.org/abs/2107.14790 - Code: None **Progressive Correspondence Pruning by Consensus Learning** - Homepage: https://sailor-z.github.io/projects/CLNet.html - Paper: https://arxiv.org/abs/2101.00591 - Code: https://github.com/sailor-z/CLNet **Energy-Based Open-World Uncertainty Modeling for Confidence Calibration** - Paper: https://arxiv.org/abs/2107.12628 - Code: None **Generalized Shuffled Linear Regression** - Paper: https://drive.google.com/file/d/1Qu21VK5qhCW8WVjiRnnBjehrYVmQrDNh/view?usp=sharing - Code: https://github.com/SILI1994/Generalized-Shuffled-Linear-Regression **Discovering 3D Parts from Image Collections** - Homepage: https://chhankyao.github.io/lpd/ - Paper: https://arxiv.org/abs/2107.13629 **Semi-Supervised Active Learning with Temporal Output Discrepancy** - Paper: https://arxiv.org/abs/2107.14153 - Code: https://github.com/siyuhuang/TOD **Why Approximate Matrix Square Root Outperforms Accurate SVD in Global Covariance Pooling?** Paper: https://arxiv.org/abs/2105.02498 Code: https://github.com/KingJamesSong/DifferentiableSVD **Hand-Object Contact Consistency Reasoning for Human Grasps Generation** - Homepage: https://hwjiang1510.github.io/GraspTTA/ - Paper(Oral): https://arxiv.org/abs/2104.03304 - Code: None **Equivariant Imaging: Learning Beyond the Range Space** - Paper(Oral): https://arxiv.org/abs/2103.14756 - Code: https://github.com/edongdongchen/EI **Just Ask: Learning to Answer Questions from Millions of Narrated Videos** - Paper(Oral): https://arxiv.org/abs/2012.00451 - Code: https://github.com/antoyang/just-ask