# CV_PaperDaily **Repository Path**: mirrors_ming71/CV_PaperDaily ## Basic Information - **Project Name**: CV_PaperDaily - **Description**: CV 论文笔记 - **Primary Language**: Unknown - **License**: Not specified - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 1 - **Forks**: 0 - **Created**: 2022-01-10 - **Last Updated**: 2026-02-09 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # CV--PaperDaily Updated at irregular intervals. Notes are attached to PDF files. # Archive ## 2022 - [TMM] Latent Feature Pyramid Network for Object Detection --- ## 2021 * [AAAI] Learning Modulated Loss for Rotated Object Detection * [AAAI] R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object * [ICCV] Reconcile Prediction Consistency for Balanced Object Detection * [CVPR] You Only Look One-level Feature * [CVPR] Boundary IoU: Improving Object-Centric Image Segmentation Evaluation * [CVPR] Coordinate Attention for Efficient Mobile Network Design * [CVPR] Dot Distance for Tiny Object Detection in Aerial Images * [CVPR] IQDet: Instance-wise Quality Distribution Sampling for Object Detection * [ICML] Rethinking Rotated Object Detection with Gaussian Wasserstein Distance Loss * [ICLR] Deformable DETR: Deformable Transformers for End-to-End Object Detection * [WACV] Disentangled Contour Learning for Quadrilateral Text Detection * [BMVC] Mask-aware IoU for Anchor Assignment in Real-time Instance Segmentation * [NeurIPS] Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression * [NeurIPS] Dynamic Resolution Network * [IROS] Object-to-Scene: Learning to Transfer Object Knowledge to Indoor Scene Recognition * [ACM MM] Decoupled IoU Regression for Object Detection * [JSTARS] Arbitrary-Oriented Ship Detection through Center-Head Point Extraction * [TIP] GSDet: Object Detection in Aerial Images Based on Scale Reasoning * [TIP] HCE: Hierarchical Context Embedding for Region-Based Object Detection * [TGRS] SKNet: Detecting Rotated Ships as Keypoints in Optical Remote Sensing Images * [TGRS] Laplacian Feature Pyramid Network for Object Detection in VHR Optical Remote Sensing Images * [NCAA] Hilbert sEMG data scanning for hand gesture recognition based on deep learning * [IVC] Weighted boxes fusion: Ensembling boxes from different object detection models * [Knowledge-Based Systems] PRPN: Progressive region prediction network for natural scene text detection * Confidence Propagation Cluster: Unleash Full Potential of Object Detectors * FAIR1M: A Benchmark Dataset for Fine-grained Object Recognition in High-Resolution Remote Sensing Imagery * Object Detection in Aerial Images A Large-Scale Benchmark and Challenges * Gaussian Guided IoU: A Better Metric for Balanced Learning on Object Detection * MOD: Benchmark for Military Object Detection * Location-Sensitive Visual Recognition with Cross-IOU Loss * Anchor Pruning for Object Detection * SCALoss: Side and Corner Aligned Loss for Bounding Box Regression --- ## 2020 * [AAAI] Arbitrary-Oriented Object Detection with Circular Smooth Label * [AAAI] CBNet: A Novel Composite Backbone Network Architecture for Object Detection * [AAAI] Distance-IoU * [AAAI] Progressive Feature Polishing Network for Salient Object Detection * [BMVC] Cascade RetinaNet: Maintaining Consistency for Single-Stage Object Detection * [CVPR] AugFPN: Improving Multi-scale Feature Learning for Object Detection * [CVPR] ContourNet: Taking a Further Step toward Accurate Arbitrary-shaped Scene Text Detection * [CVPR] Delving into Online High-quality Anchors Mining for Detecting Outer Faces * [CVPR] Detection in Crowded Scenes One Proposal, Multiple Predictions * [CVPR] Learning from Noisy Anchors for One-stage Object Detection * [CVPR] Multiple Anchor Learning for Visual Object Detection * [CVPR] PolarMask: Single Shot Instance Segmentation with Polar Representation * [CVPR] Revisiting the Sibling Head in Object Detector * [ECCV] Dynamic R-CNN : Towards High Quality Object Detection via Dynamic Training * [ECCV] PIoU Loss: Towards Accurate Oriented Object Detection in Complex Environments * [ECCV] Probabilistic Anchor Assignment with IoU Prediction for Object Detection * [ECCV] Rotation-robust Intersection over Union for 3D Object Detection * [ECCV] End-to-End Object Detection with Transformers * [ECCV] Side-Aware Boundary Localization for More Precise Object Detection * [JSTARS] Learning Point-guided Localization for Detection in Remote Sensing Images * [TGRS] Adaptive Period Embedding for Representing Oriented Objects in Aerial Images * [TCSVT] Joint Anchor-Feature Refinement for Real-Time Accurate Object Detection in Images and Videos * [Neurocomputing] Recent Advances in Deep Learning for Object Detection * [Neurocomputing] Single-Shot Bidirectional Pyramid Networks for High-Quality Object Detection * [Remote Sens.] EFN: Field-based Object Detection for Aerial Images * [Remote Sens.] Single-Stage Rotation-Decoupled Detector for Oriented Object * [Remote Sens.] A2S-Det: Efficiency Anchor Matching in Aerial Image Oriented Object Detection * [WACV] Improving Object Detection with Inverted Attention * [WACV] Propose-and-Attend Single Shot Detector * Align Deep Features for Oriented Object Detection * AMRNet: Chips Augmentation in Areial Images Object Detection * BBRefinement: An universal scheme to improve precision of box object detectors * Conditional Convolutions for Instance Segmentation * Cross-layer Feature Pyramid Network for Salient Object Detection * EAGLE: Large-scale Vehicle Detection Dataset inReal-World Scenarios using Aerial Imagery * Extended Feature Pyramid Network for Small Object Detection * FeatureNMS: Non-Maximum Suppression by Learning Feature Embeddings * Feature Pyramid Grids * IterDet: Iterative Scheme for ObjectDetection in Crowded Environments * Location-Aware Feature Selection for Scene Text Detection * Objects detection for remote sensing images based on polar coordinates * Scale-Invariant Multi-Oriented Text Detection in Wild Scene Images * Scaled-YOLOv4: Scaling Cross Stage Partial Network --- ## 2019 * [AAAI] Gradient Harmonized Single-stage Detector * [AAAI] M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid * [BMVC] Rethinking Classification and Localization for Cascade R-CNN * [CVPR] Assisted Excitation of Activations: A Learning Technique to Improve Object * [CVPR] Borrow from Anywhere Pseudo Multi-modal Object Detection in Thermal Imagery * [CVPR] Dual Attention Network for Scene Segmentation * [CVPR] Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression * [CVPR] Learning RoI Transformer for Detecting Oriented Objects in Aerial Images * [CVPR] Learning Instance Activation Maps for Weakly Supervised Instance Segmentation * [CVPR] Libra R-CNN: Towards Balanced Learning for Object Detection * [CVPR] Panoptic Segmentation * [CVPR] Region Proposal by Guided Anchoring * [CVPR] ScratchDet : Training Single-Shot Object Detectors * [CVPR] Softer-NMS: Rethinking Bounding Box Regression for Accurate Object Detection * [CVPR] Spatial-aware Graph Relation Network for Large-scale Object Detection * [CVPR] Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations * [ICCV] Dynamic Multi-scale Filters for Semantic Segmentation * [ICCV] EGNet: Edge Guidance Network for Salient Object Detection * [ICCV] FCOS: Fully Convolutional One-Stage Object Detection * [ICCV] InstaBoost: Boosting Instance Segmentation via Probability Map Guided * [ICCV] Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty for Autonomous Driving * [ICCV] Matrix Nets: A New Deep Architecture for Object Detection * [ICCV] ThunderNet: Towards Real-time Generic Object Detection * [ICCV] Towards More Robust Detection for Small, Cluttered and Rotated Objects * [ICCV] Scale-Aware Trident Networks for Object Detection * [ICCV] SCRDet: Towards More Robust Detection for Small, Cluttered and Rotated Objects * [ICIP] SSSDET: Simple Short and Shallow Network for Resource Efficient Vehicle Detection in Aerial Scenes * [ICLR] Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet * [ICLR] ImageNet-trained CNNs are biased towards texture: increasing shape bias improves accuracy and robustness * [ICLR] Why do deep convolutional networks generalize so poorly to small image transformations? * [ICML] How much real data do we actually need: Analyzing object detection performance using synthetic and real data * [ICML] Making Convolutional Networks Shift-Invariant Again * [ICTAI] Twin Feature Pyramid Networks for Object Detection * [IEEE Access] A Real-Time Scene Text Detector with Learned Anchor * [IEEE Trans Geosci Remote Sens] CAD-Net: A Context-Aware Detection Network for Objects in Remote Sensing Imagery * [IJCAI] Omnidirectional Scene Text Detection with Sequential-free Box Discretization * [J. Big Data] A survey on Image Data Augmentation for Deep Learning * [NeurIPS] Cascade RPN Delving into High-Quality Region Proposal Network with Adaptive Convolution * [NeurIPS] FreeAnchor Learning to Match Anchors for Visual Object Detection * A Preliminary Study on Data Augmentation of Deep Learning for Image Classification * Bag of Freebies for Training Object Detection Neural Networks * Consistent Optimization for Single-Shot Object Detection * Deep Learning for 2D and 3D Rotatable Data An Overview of Methods * Double-Head RCNN: Rethinking Classification and Localization for Object Detection * IENet: Interacting Embranchment One Stage Anchor Free Detector for Orientation Aerial Object Detection * IoU-uniform R-CNN: Breaking Through the Limitations of RPN * Is Sampling Heuristics Necessary in Training Deep Object Detectors * Learning Data Augmentation Strategies for Object Detection * Learning from Noisy Anchors for One-stage Object Detection * Light-Head R-CNN: In Defense of Two-Stage Object Detector * MMDetection: Open MMLab Detection Toolbox and Benchmark * Multi-Scale Attention Network for Crowd Counting * Natural Adversarial Examples * Needles in Haystacks: On Classifying Tiny Objects in Large Images * Revisiting Feature Alignment for One-stage Object Detection * Ship Detection: An Improved YOLOv3 Method --- ## 2018 * [ACCV] Reverse Densely Connected Feature Pyramid Network for Object Detection * [BMVC] Enhancement of SSD by concatenating feature maps for object detection * [CVPR] An Analysis of Scale Invariance in Object Detection * [CVPR] Cascade R-CNN: Delving into High Quality Object Detection * [CVPR] DOTA: A Large-scale Dataset for Object Detection in Aerial Images * [CVPR] Path Aggregation Network for Instance Segmentation * [CVPR] Pseudo Mask Augmented Object Detection * [CVPR] Rotation Sensitive Regression for Oriented Scene Text Detection * [CVPR] Scale-Transferable Object Detection * [CVPR] Single-Shot Object Detection with Enriched Semantics * [CVPR] Single-Shot Refinement Neural Network for Object Detection * [CVPR] Squeeze-and-Excitation Networks * [CVPR] Weakly Supervised Instance Segmentation using Class Peak Response * [ECCV] Acquisition of Localization Confidence for Accurate Object Detection * [ECCV] Deep Feature Pyramid Reconfiguration for Object Detection * [ECCV] DetNet: A Backbone network for Object Detection * [ECCV] Learning to Segment via Cut-and-Paste * [ECCV] Modeling Visual Context is Key to Augmenting Object Detection Datasets * [ECCV] Receptive Field Block Net for Accurate and Fast Object Detection * [ICLR] Multi-Scale Dense Convolutional Networks for Efficient Prediction * [ICANN] Further advantages of data augmentation on convolutional neural networks * [ISBI] A Novel Focal Tversky loss function with improved Attention U-Net for lesion segmentation * [TIP] TextBoxes++: A single-shot oriented scene text detector * [TMM] Arbitrary-oriented scene text detection via rotation proposals * [IJAC] An Overview of Contour Detection Approaches * [IJCV] What Makes Good Synthetic Training Data for Learning Disparity and Optical Flow Estimation? * [J Mach Learn Res] Neural Architecture Search: A Survey * [Remote Sens.] Automatic Ship Detection of Remote Sensing Images from Google Earth in Complex Scenes Based on Multi-Scale Rotation Dense Feature Pyramid Networks * [VISIGRAPP] Learning Transformation Invariant Representations with Weak Supervision * [WACV] Understanding Convolution for Semantic Segmentation * Data Augmentation by Pairing Samples for Images Classification * MDSSD: Multi-scale Deconvolutional Single Shot Detector for Small Objects * RAM: Residual Attention Module for Single Image Super-Resolution * R2CNN: Rotational Region CNN for Orientation Robust Scene Text Detection --- ## 2017 * [AAAI] Weakly Supervised Semantic Segmentation Using Superpixel Pooling Network * [CVPR] Feature Pyramid Networks for Object Detection * [CVPR] Not All Pixels Are Equal: Difficulty-Aware Semantic Segmentation via Deep Layer Cascade * [CVPR] Oriented Response Networks * [CVPR] Simple Does It: Weakly Supervised Instance and Semantic Segmentation * [ICCV] Cut, Paste and Learn: Surprisingly Easy Synthesis for Instance Detection * [ICCV] Focal Loss for Dense Object Detection * [ICCV] Grad-CAM Visual Explanations From Deep Networks via Gradient-Based Localization * [ICCV] Single shot scale-invariant face detector * [ICCV] Single Shot Text Detector with Regional Attention * [ICIP] Rotated region based CNN for ship detection * [ICLR] Dataset Augmentationin In Feature Space * [ICPRAM] A High Resolution Optical Satellite Image Dataset for Ship Recognition and Some New Baselines * [IEEE Acess] Smart Augmentation: Learning an Optimal Data Augmentation Strategy * FSSD: Feature Fusion Single Shot Multibox Detector * Improved Regularization of Convolutional Neural Networks with Cutout * The Effectiveness of Data Augmentation in Image Classification using Deep Learning * Tversky loss function for image segmentation using 3D fully convolutional deep networks --- ## 2016 * [CVPR] Learning Deep Features for Discriminative Localization * [DICTA] Understanding data augmentation for classification: when to warp? * [ECCV] Contextual Priming and Feedback for Faster R-CNN * [NIPS] R-FCN: Object Detection via Region-based Fully Convolutional Networks * [GRSL] Ship Rotated Bounding Box Space for Ship Extraction From High-Resolution Optical Satellite Images With Complex Backgrounds * Beyond Skip Connections: Top-Down Modulation for Object Detection --- ## 2015 * [ICDAR] ICDAR 2015 competition on Robust Reading --- ## 2014 * [CVPR] Scalable Object Detection Using Deep Neural Networks --- ## 2012 * [PAMI] Measuring the Objectness of Image Windows --- ## 2009 * [ICML] Curriculum learning --- ## 2000 * [IJCV] The earth mover's distance as a metric for image retrieval