himalayajain's Stars
valeoai/ADVENT
Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation
valeoai/QuEST
boschresearch/OASIS
Official implementation of the paper "You Only Need Adversarial Supervision for Semantic Image Synthesis" (ICLR 2021)
mseitzer/pytorch-fid
Compute FID scores with PyTorch.
rosasalberto/StyleGAN2-TensorFlow-2.x
Unofficial implementation of StyleGAN2 using TensorFlow 2.x.
MiaoyunZhao/GANmemory_LifelongLearning
tkarras/progressive_growing_of_gans
Progressive Growing of GANs for Improved Quality, Stability, and Variation
Puzer/stylegan-encoder
StyleGAN Encoder - converts real images to latent space
yccyenchicheng/pytorch-WGAN-GP-TTUR-CelebA
akanimax/BMSG-GAN
[MSG-GAN] Any body can GAN! Highly stable and robust architecture. Requires little to no hyperparameter tuning. Pytorch Implementation
akanimax/msg-stylegan-tf
MSG StyleGAN in tensorflow
NVlabs/stylegan
StyleGAN - Official TensorFlow Implementation
valeoai/DADA
Depth-aware Domain Adaptation in Semantic Segmentation
willylulu/celeba-hq-modified
Modified h5tool.py make user getting celeba-HQ easier
nperraud/download-celebA-HQ
Python script to download the celebA-HQ dataset from google drive
sseung0703/KD_methods_with_TF
Knowledge distillation methods implemented with Tensorflow (now there are 11 (+1) methods, and will be added more.)
szagoruyko/attention-transfer
Improving Convolutional Networks via Attention Transfer (ICLR 2017)
HobbitLong/RepDistiller
[ICLR 2020] Contrastive Representation Distillation (CRD), and benchmark of recent knowledge distillation methods
eriklindernoren/PyTorch-GAN
PyTorch implementations of Generative Adversarial Networks.
lanpa/tensorboardX
tensorboard for pytorch (and chainer, mxnet, numpy, ...)
wasidennis/AdaptSegNet
Learning to Adapt Structured Output Space for Semantic Segmentation, CVPR 2018 (spotlight)
technicolor-research/subic
Tensorflow implementation of a supervised approach to learn highly compressed image representations
himalayajain/subic
Tensorflow implementation of a supervised approach to learn highly compressed image representations