Precinct shapes (and vote results) for US elections past, present, and future

convert dataset to coco/voc format

[NeurIPS2021] Code Release of K-Net: Towards Unified Image Segmentation

Ultralytics YOLO11 🚀

deep learning for image processing including classification and object-detection etc.

[CVPR 2023] Official implementation of the paper "Mask DINO: Towards A Unified Transformer-based Framework for Object Detection and Segmentation"

Implementation of paper - YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information

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

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use th…

OpenMMLab Semantic Segmentation Toolbox and Benchmark.

Mask Transfiner for High-Quality Instance Segmentation, CVPR 2022

OpenMMLab YOLO series toolbox and benchmark. Implemented RTMDet, RTMDet-Rotated,YOLOv5, YOLOv6, YOLOv7, YOLOv8,YOLOX, PPYOLOE, etc.

Deformable Convolutional Networks v2 with Pytorch

A simple, fully convolutional model for real-time instance segmentation.

[CVPR 2024 - Oral] Matching 2D Images in 3D: Metric Relative Pose from Metric Correspondences

OpenMMLab Detection Toolbox and Benchmark

SOLO and SOLOv2 for instance segmentation, ECCV 2020 & NeurIPS 2020.

This is an unofficial implementation of the Point Transformer paper.

Point Transformers

[CVPR'24 Oral] Official repository of Point Transformer V3 (PTv3)

OpenPCSeg: Open Source Point Cloud Segmentation Toolbox and Benchmark

[NeurIPS'23 Spotlight] Segment Any Point Cloud Sequences by Distilling Vision Foundation Models

Semantic and Instance Segmentation of LiDAR point clouds for autonomous driving

SOTA fast and robust ground segmentation using 3D point cloud (accepted in RA-L'21 w/ IROS'21)

Ground Segmentation from Lidar Point Clouds

Uncertainty-aware Semantic Segmentation of LiDAR Point Clouds for Autonomous Driving

Implementation of SqueezeSeg, convolutional neural networks for LiDAR point clout segmentation

PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.