Pinned Repositories
disentanglement_dataset
AIRCAP
Aerial Outdoor Motion Capture - Public Code Repository
amazon-sagemaker-examples
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
awesome-causality-algorithms
An index of algorithms for learning causality with data
awesome-deep-vision
A curated list of deep learning resources for computer vision
cats_vs_dogs
This is the implementation to solve Kaggle's cat vs dog segregation.
pytorch-ssim
pytorch structural similarity (SSIM) loss
save-deep
Save activations in response to images for specified layers of Caffe-format deep neural network models
Texture-based-Super-Resolution-Network
Pytorch implementation of Texture based Super-resolution Networks
weakly_supervised_localizations_tf
CNNs based weakly supervised localizations in Tensorflow
waleedgondal's Repositories
waleedgondal/Texture-based-Super-Resolution-Network
Pytorch implementation of Texture based Super-resolution Networks
waleedgondal/weakly_supervised_localizations_tf
CNNs based weakly supervised localizations in Tensorflow
waleedgondal/cats_vs_dogs
This is the implementation to solve Kaggle's cat vs dog segregation.
waleedgondal/AIRCAP
Aerial Outdoor Motion Capture - Public Code Repository
waleedgondal/amazon-sagemaker-examples
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
waleedgondal/awesome-causality-algorithms
An index of algorithms for learning causality with data
waleedgondal/capsule-networks
A PyTorch implementation of the NIPS 2017 paper "Dynamic Routing Between Capsules".
waleedgondal/ConvCRF
This repository contains the reference implementation for our proposed Convolutional CRFs.
waleedgondal/deep-image-prior
Image restoration with neural networks but without learning.
waleedgondal/deep-photo-styletransfer-tf
Tensorflow (Python API) implementation of Deep Photo Style Transfer
waleedgondal/disentanglement_lib
disentanglement_lib is an open-source library for research on learning disentangled representations.
waleedgondal/EnhanceNet
Pytorch Implementation of EnhanceNet
waleedgondal/FastPhotoStyle
Style transfer, deep learning, feature transform
waleedgondal/GEM
waleedgondal/generative-query-network-pytorch
Generative Query Network (GQN) in PyTorch as described in "Neural Scene Representation and Rendering"
waleedgondal/genesis
Official PyTorch implementation of "GENESIS: Generative Scene Inference and Sampling with Object-Centric Latent Representations"
waleedgondal/l4-pytorch
L4: Practical loss-based stepsize adaptation for PyTorch
waleedgondal/lcp-physics
A differentiable LCP physics engine in PyTorch.
waleedgondal/nerf
Code release for NeRF (Neural Radiance Fields)
waleedgondal/neurips2019_disentanglement_challenge_starter_kit
Starter Kit for the NeurIPS 2019 Disentanglement Challenge
waleedgondal/nmp_qc
Neural Message Passing for Computer Vision
waleedgondal/NRI
Neural relational inference for interacting systems - pytorch
waleedgondal/PerceptualSimilarity
Learned Perceptual Image Patch Similarity (LPIPS) metric and Berkeley-Adobe Perceptual Patch Similarity (BAPPS) dataset
waleedgondal/pytorch-SRDenseNet
Pytorch implementation for SRDenseNet (ICCV2017)
waleedgondal/RL-Adventure-2
PyTorch0.4 implementation of: actor critic / proximal policy optimization / acer / ddpg / twin dueling ddpg / soft actor critic / generative adversarial imitation learning / hindsight experience replay
waleedgondal/SRGAN
A PyTorch implementation of SRGAN based on the paper "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network"
waleedgondal/srgan-1
Pytorch implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network"
waleedgondal/TCN
Sequence modeling benchmarks and temporal convolutional networks
waleedgondal/video-super-resolution
Video super resolution implemented in Pytorch
waleedgondal/visual-interaction-networks-pytorch
This's an implementation of deepmind Visual Interaction Networks paper using pytorch