Deep Learning

Frameworks for Neural Networks and Deep Learning.

Newest releases

drorlab Geometric Vector Perceptrons --- a rotation-equivariant GNN for learning from biomolecular structure

isaaccorley PyTorch implementation of "MLP-Mixer: An all-MLP Architecture for Vision" Tolstikhin et al. (2021)

serengil RetinaFace is the face detection module of insightface project. The original implementation is mainly based on mxnet. Then, its tensorflow based re-implementation is published by Stanislas Bertrand.

cvzone This is a Computer vision package that makes its easy to run Image processing and AI functions. At the core it uses OpenCV and Mediapipe libraries.

vaseline555 An unofficial implementation of FederatedAveraging (or FedAvg) algorithm proposed in the paper Communication-Efficient Learning of Deep Networks from Decentralized Data in PyTorch

rabbityl DeformingThings4D is an synthetic dataset containing 1,972 animation sequences spanning 31 categories of humanoids and animals.

dkappe Is this lc0? Definitely not. Lc0 is a clone of alpha zero chess, based on the paper by Deep Mind. Also, lc0 is a somewhat complicated, brittle bit of C++ code that runs into the thousand of lines. A0lite, by contrast, is a very si

lyricat A list of awesome things related to Mixin Network

Atharva-Phatak TorchFlare is a simple, beginner-friendly and an easy-to-use PyTorch Framework train your models without much effort. It provides an almost Keras-like experience for training your models with all the callbacks, metrics, etc

jiangtaoxie The Vision Transformer (ViT) heavily depends on pretraining using ultra large-scale datasets (e.g. ImageNet-21K or JFT-300M) to achieve high performance, while significantly underperforming on ImageNet-1K if trained from scratch.

CS-GangXu This is the official PyTorch implementation of TMNet in the CVPR 2021 paper "Temporal Modulation Network for Controllable Space-Time Video Super-Resolution". Our TMNet can flexibly interpolate intermediate frames for space-time vi

zyxxmu Pytorch implementation of our paper under review — Lottery Jackpots Exist in Pre-trained Models

Python3WebSpider Deep LearningImage Captcha 2

TeaPearce ArXiv paper 'Counter-Strike Deathmatch with Large-Scale Behavioural Cloning'

PeizhuoLi An end-to-end library for automatic character rigging, skinning, and blend shapes generation, as well as a visualization tool. [SIGGRAPH 2021]

hujiecpp ISTR: End-to-End Instance Segmentation with Transformers

Duankaiwen The trained models are temporarily unavailable, but you can train the code using reasonable computational resource.

enriccorona Implementation for the paper SMPLicit: Topology-aware Generative Model for Clothed People (CVPR 2021)

michiyasunaga QA-GNN: Question Answering using Language Models and Knowledge Graphs

Mukosame Anime2Sketch: A sketch extractor for illustration, anime art, manga

geekjr QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.

AIcrowd Starter kit for getting started in the Music Demixing Challenge.

sradc SmallPebble is a minimal automatic differentiation and deep learning library written from scratch in Python, using NumPy/CuPy.

ebartrum GAN models (including 3D controllable models) implemented with Pytorch Lightning and Hydra configuration.

facebookresearch PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO

yinyunie This library includes the tools for rendering multi-view color and depth images of ShapeNet models. Physically based rendering (PBR) is featured based on blender2.79.

zinuok This is the dataset for testing the robustness of various VO/VIO methods

zfchenUnique This repo contains the pytorch implementation for Dynamic Concept Learner (accepted by ICLR 2021).

Colin97 DeepMetaHandles is a shape deformation technique. It learns a set of meta-handles for each given shape. The disentangled meta-handles factorize all the plausible deformations of the shape, while each of them corresponds to an intu

locuslab DC3: A Learning Method for Optimization with Hard Constraints

Meituan-AutoML Very recently, a variety of vision transformer architectures for dense prediction tasks have been proposed and they show that the design of spatial attention is critical to their success in these tasks

junzhezhang [CVPR 2021] Unsupervised 3D Shape Completion through GAN Inversion

Jia-Research-Lab This project provides the implementation for the CVPR 2021 paper "Scale-aware Automatic Augmentation for Object Detection". Scale-aware AutoAug provides a new search space and search metric to find effective data agumentation poli