Dual Attention Network for Scene Segmentation (CVPR2019)
CVPR2021 Workshop - HDRUNet: Single Image HDR Reconstruction with Denoising and Dequantization.
micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、Low-Bit(≤2b)/Ternary and Binary(TWN/BNN/XNOR-Net); post-training-quantization(PTQ), 8-bit(tensorrt); 2、 pruning: normal、regular and group convolutional channel pruning; 3、 group convolution structure; 4、batch-normalization fuse for quantization. deploy: tensorrt, fp32/fp16/int8(ptq-calibration)、op-adapt(upsample)、dynamic_shape
Official repository for "Multi-Stage Progressive Image Restoration" (CVPR 2021). SOTA results for Image deblurring, deraining, and denoising.
Collection of popular and reproducible image denoising works.
Learning Image-adaptive 3D Lookup Tables for High Performance Photo Enhancement in Real-time
unofficial inplementation of paper Underexposed Photo Enhancement using Deep Illumination Estimation(2019 CVPR)
Video quality metrics, reference implementation in python: VIF, SSIM, PSNR, ...
Unofficial PyTorch code for the paper - Deep Retinex Decomposition for Low-Light Enhancement, BMVC'18
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Semantic Segmentation.
this is the official code for the paper "Retinex-inspired Unrolling with Cooperative Prior Architecture Search for Low-light Image Enhancement"
The pytorch implementation of RetinexDIP, a unified zero-reference deep framework for low-light enhancement.