Differentiable architecture search for convolutional and recurrent networks

Neural Architecture Search Without Training

Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-Supervision (CVPR 2020 Oral)

Few Shot

real-time network architecture for mobile devices and semantic segmentation

AAAI 2019 paper. "Residual Invertible Spatio-Temporal Network for Video Super-Resolution"

Implementation of “LatentGNN: Learning Efficient Non-local Relations for Visual Recognition”(ICML 2019)

PyTorch implementation of Grad-CAM

Semantic Segmentation Architectures Implemented in PyTorch

Learning Pixel-level Semantic Affinity with Image-level Supervision for Weakly Supervised Semantic Segmentation, CVPR 2018

DSB2018 [ods.ai] topcoders

Feature selector is a tool for dimensionality reduction of machine learning datasets

A course in reinforcement learning in the wild

Caffe implementation of "Fast and Accurate Single Image Super-Resolution via Information Distillation Network"

Pyramid Stereo Matching Network (CVPR2018)

Codes and datasets for 'Cross-Domain Weakly-Supervised Object Detection through Progressive Domain Adaptation' [Inoue+, CVPR2018].

Generative Image Inpainting with Contextual Attention https://arxiv.org/abs/1801.07892, demo http://jhyu.me/demo

A collection of funny cvpr2018 project

Densely Connected Pyramid Dehazing Network (CVPR'2018)

Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification (https://arxiv.org/pdf/1711.07027.pdf). CVPR2018

Models and examples built with TensorFlow

Implementation of our accepted CVPR 2018 paper "Rethinking Feature Distribution for Loss Functions in Image Classification"

Resources of semantic segmantation based on Deep Learning model

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

Official implementation of Paper Future Frame Prediction for Anomaly Detection -- A New Baseline, CVPR 2018

a pytorch code about Residual Attention Network. This code is based on two projects from