Noire

mmsegmentation

OpenMMLab Semantic Segmentation Toolbox and Benchmark.

pytorch-OpCounter

Count the MACs / FLOPs of your PyTorch model.

flops-counter.pytorch

Flops counter for convolutional networks in pytorch framework

cityscapesScripts

README and scripts for the Cityscapes Dataset

torchstat

Model analyzer in PyTorch

Awesome-VAEs

A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.

ISDA-for-Deep-Networks

An efficient implicit semantic augmentation method, complementary to existing non-semantic techniques.

MMT

[ICLR-2020] Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification.

CDAN

Code release for "Conditional Adversarial Domain Adaptation" (NIPS 2018)

VAT-pytorch

Virtual Adversarial Training (VAT) implementation for PyTorch

pixel-level-contrastive-learning

Implementation of Pixel-level Contrastive Learning, proposed in the paper "Propagate Yourself", in Pytorch

DA_dahazing

Domain Adaptation for Image Dehazing, CVPR2020

DSBN

Official Implementation of "Domain Specific Batch Normalization for Unsupervised Domain Adaptation (CVPR2019)"

Curriculum-Labeling

[AAAI 2021] Curriculum Labeling: Revisiting Pseudo-Labeling for Semi-Supervised Learning

fog_simulation-SFSU_synthetic

Pixel-Level-Cycle-Association

Pytorch Implementation for NeurIPS (oral) paper: Pixel Level Cycle Association: A New Perspective for Domain Adaptive Semantic Segmentation

Neural-Style-MMD

MXNet Code For Demystifying Neural Style Transfer (IJCAI 2017)

uda_release

Unsupervised Domain Adaptation through Self-Supervision

deep_constrained_clustering

invert

PyTorch implementation of Mahendran & Vedaldi, 2015: "Understanding Deep Image Representations by Inverting Them"

clsa_pytorch

Unofficial implement of CLSA(Contrastive Learning with Stronger Augmentations) with minimum modifications on official moco's code

Data-Free_Network_Quantization_With_Adversarial_Knowledge_Distillation

Data-Free Network Quantization With Adversarial Knowledge Distillation PyTorch

3DRealisticSceneDehaze

Code for Learning to Dehaze From Realistic Scene with A Fast Physics Based Dehazing Network

Data-Free-Learning-of-Student-Networks

VMT

ESL

ESL: Entropy-guided Self-supervised Learning for Domain Adaptation in Semantic Segmentation

Dual-Mixup-Regularized-Learning-for-Adversarial-Domain-Adaptation

Implementation of "Dual Mixup Regularized Learning for Adversarial Domain Adaptation" in Pytorch

CCADA

Joint Contrastive Learning for Unsupervised Domain Adaptation

NIPS_2019_Reproducibilty_Challenge_Zero-shot_Knowledge_Transfer_via_Adversarial_Belief_Matching

DeepInversion