Detectron2 is FAIR's next-generation platform for object detection, segmentation and other visual recognition tasks.

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

AdelaiDet is an open source toolbox for multiple instance-level detection and recognition tasks.

OpenMMLab Video Perception Toolbox. It supports Single Object Tracking (SOT), Multiple Object Tracking (MOT), Video Object Detection (VID) with a unified framework.

A simple baseline for one-shot multi-object tracking

HOTA (and other) evaluation metrics for Multi-Object Tracking (MOT).

ByteTrack: Multi-Object Tracking by Associating Every Detection Box

An easy to understand and better performance version of CenterNet

Code for the head detector (HeadHunter) proposed in our CVPR 2021 paper Tracking Pedestrian Heads in Dense Crowd.

Deformable Convolutional Networks v2 with Pytorch

End-to-End Object Detection with Learnable Proposal

A curated list of awesome self-supervised methods

COCO API - Dataset @ http://cocodataset.org/

The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"

Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.

Tensors and Dynamic neural networks in Python with strong GPU acceleration

A real-time approach for mapping all human pixels of 2D RGB images to a 3D surface-based model of the body

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

Faster R-CNN (Python implementation) -- see https://github.com/ShaoqingRen/faster_rcnn for the official MATLAB version

Caffe: a fast open framework for deep learning.

Faster R-CNN

My resume, generated with moderncv

Programming exercises for the Stanford Unsupervised Feature Learning and Deep Learning Tutorial