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A natural language interface for computers
OpenMMLab Detection Toolbox and Benchmark
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
End-to-End Object Detection with Transformers
Toolkit for linearizing PDFs for LLM datasets/training
🐍 Geometric Computer Vision Library for Spatial AI
A collaboration friendly studio for NeRFs
PyTorch3D is FAIR's library of reusable components for deep learning with 3D data
OpenMMLab Semantic Segmentation Toolbox and Benchmark.
Anomaly detection related books, papers, videos, and toolboxes
Faster R-CNN (Python implementation) -- see https://github.com/ShaoqingRen/faster_rcnn for the official MATLAB version
A PyTorch implementation of EfficientNet
A faster pytorch implementation of faster r-cnn
Object detection, 3D detection, and pose estimation using center point detection:
PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO
OpenMMLab Pose Estimation Toolbox and Benchmark.
ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution
OpenMMLab's next-generation platform for general 3D object detection.
A PyTorch implementation of NeRF (Neural Radiance Fields) that reproduces the results.
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
Most popular metrics used to evaluate object detection algorithms.
A PyTorch Library for Accelerating 3D Deep Learning Research
Manipulation and analysis of geometric objects
[ECCV 2022] This is the official implementation of BEVFormer, a camera-only framework for autonomous driving perception, e.g., 3D object detection and semantic map segmentation.
STUMPY is a powerful and scalable Python library for modern time series analysis
OpenMMLab Video Perception Toolbox. It supports Video Object Detection (VID), Multiple Object Tracking (MOT), Single Object Tracking (SOT), Video Instance Segmentation (VIS) with a unified framework.