Deep Learning

Frameworks for Neural Networks and Deep Learning.

Newest releases

JeffLIrion This package implements a Graph SLAM solver in Python.

Megvii-BaseDetection OTA: Optimal Transport Assignment for Object Detection This project provides an implementation for our CVPR2021 paper "OTA: Optimal Transport Assignme

AndrasKovacs flatparse flatparse is a high-performance parsing library, focusing on programming languages and human-readable data formats. The "flat" in the name r

zczcwh 3D Human Pose Estimation with Spatial and Temporal Transformers This repo is the official implementation for 3D Human Pose Estimation with Spatial and

daodaofr Introduction This is the implementation for Anchor-Free Person Search in CVPR2021. A brief introduction in Chinese can be found at https://zhuanlan.zh

twistedcubic Attention is not all you need, pure attention loses rank doubly exponentially with depth. Yihe Dong, Jean-Baptiste Cordonnier, Andreas Loukas. In this

chenxin-dlut TransT - Transformer Tracking [CVPR2021] Official implementation of the TransT (CVPR2021) , including training code and trained models. Tracker TransT

vinbigdata-medical The VinDr Lab is a Data Platform for Medical AI that enables building high-quality datasets and algorithms with the lean process and advanced annotati

lingtengqiu Open-PIFuhd This is a unofficial implementation of PIFuhd PIFuHD: Multi-Level Pixel-Aligned Implicit Function forHigh-Resolution 3D Human Digitization

Pose-Group Deep Dual Consecutive Network for Human Pose Estimation (CVPR2021) Paper Introduction This is the official code of Deep Dual Consecutive Network for H

Xiangtaokong (CVPR2021) ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic

princeton-nlp Code and models for the paper "A Frustratingly Easy Approach for Entity and Relation Extraction"

berniwal Implementation of the Swin Transformer in PyTorch.

bowenc0221 Boundary IoU API (Beta version)

facebookresearch Source code, datasets and trained models for the paper Learning Advanced Mathematical Computations from Examples (ICLR 2021), by François Charton, Amaury Hayat (ENPC-Rutgers) and Guillaume Lample

TACJu This is the official PyTorch implementation of the paper "TransFG: A Transformer Architecture for Fine-grained Recognition"

HongwenZhang Code for "3D Human Pose and Shape Regression with Pyramidal Mesh Alignment Feedback Loop"

Vasanthengineer4949 A project on predicting whether it will rain tomorrow or not by using the Rainfall in Australia dataset This project is tested over lot of ml models like catboost, xgboost, random forest, support vector classifier

dobrosketchkun Buckle up, adventure in the styleGAN2-ada-pytorch network latent space awaits

microsoft a general-purpose Transformer based vision backbone

lucidrains Implementation of STAM (Space Time Attention Model), yet another pure and simple SOTA attention model that bests all previous models in video classification. This corroborates the finding of TimeSformer. Attention is all we need.

researchmm AOT-GAN for High-Resolution Image Inpainting (codebase for image inpainting)

allegroai ClearML - Auto-Magical Suite of tools to streamline your ML workflow. Experiment Manager, ML-Ops and Data-Management

linhandev 医学影像数据集列表

frotms PaddleOCR inference in PyTorch. Converted from [PaddleOCR]

matthewvowels1 A curated list of awesome work on video generation and video representation learning, and related topics.

YixinChen-AI For beginner, this will be the best start for VAEs, GANs, and CVAE-GAN. This contains AE, DAE, VAE, GAN, CGAN, DCGAN, WGAN, WGAN-GP, VAE-GAN, CVAE-GAN. All use PyTorch.

lkeab Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers [CVPR 2021]

Alibaba-MIIL Official implementation of "An Image is Worth 16x16 Words, What is a Video Worth?" (2021 paper)

geaxgx Running Google Mediapipe body pose tracking models on DepthAI hardware (OAK-1, OAK-D, ...)

tinyms-ai TinyMS is an Easy-to-Use deep learning framework development toolkit based on MindSpore, designed to provide quick-start guidelines for machine learning beginners.