Object detection, 3D detection, and pose estimation using center point detection:

A conda-forge distribution.

OpenMMLab Pose Estimation Toolbox and Benchmark.

MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, …

MobileNetV1, MobileNetV2, VGG based SSD/SSD-lite implementation in Pytorch 1.0 / Pytorch 0.4. Out-of-box support for retraining on Open Images dataset. ONNX and Caffe2 support. Experiment Ideas lik…

Try out deep learning models online on Google Colab

Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.

NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥

Open3D: A Modern Library for 3D Data Processing

Efficient 3D human pose estimation in video using 2D keypoint trajectories

A deep learning library for video understanding research.

Type annotations and dynamic checking for a tensor's shape, dtype, names, etc.

Official PyTorch implementation of Spatial Dependency Networks.

Official implementation of PVT series

Official code for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)

The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!

Very deep VAEs in JAX/Flax

JAX-based neural network library

Open-Source Neural Machine Translation in Tensorflow

[ICML 2021 Oral] We show pure attention suffers rank collapse, and how different mechanisms combat it.

VISSL is FAIR's library of extensible, modular and scalable components for SOTA Self-Supervised Learning with images.

Official Implementation for "StyleCLIP: Text-Driven Manipulation of StyleGAN Imagery" (ICCV 2021 Oral)

This repo contains the scripts, models, and required files for the Deep Noise Suppression (DNS) Challenge.

Uplift modeling and causal inference with machine learning algorithms

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

A community-maintained Python framework for creating mathematical animations.

Pretrained efficient transformers on genomes -- WIP

Convolution visualizations

Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.

Deep Learning Visualization Toolkit（『飞桨』深度学习可视化工具 ）