Xiangtai Li's Projects
Pytorch implementation of newly added convolution
Implementation of "PifPaf: Composite Fields for Human Pose Estimation" in PyTorch.
Benchmarking Panoptic Scene Graph Generation (PSG), ECCV'22
Python optical flow visualization following Baker et al. (ICCV 2007) as used by the MPI-Sintel challenge
This is the official PyTorch implementation of the paper Open-Vocabulary Semantic Segmentation with Mask-adapted CLIP.
A new framework for open-vocabulary object detection, based on maskrcnn-benchmark
End-to-end image segmentation kit based on PaddlePaddle.
This is Pytorch re-implementation of our CVPR 2020 paper "Panoptic-DeepLab: A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic Segmentation" (https://arxiv.org/abs/1911.10194)
The First Unified End-to-End System for Panoptic Part Segmentation-ECCV-2022
COCO 2018 Panoptic Segmentation Task API (Beta version)
this repo records the latest paper in Computer Vision
PointFlow (CVPR-2021)
LaTeX template for dissertations in Peking University
Training code for "Associative Embedding: End-to-End Learning for Joint Detection and Grouping"
Code for the paper "Pose2Seg: Detection Free Human Instance Segmentation" @ CVPR2019.
PoseFlow: Efficient Online Pose Tracking (BMVC'18)
Evaluation of multi-person pose estimation and tracking
Precise RoI Pooling with coordinate gradient support, proposed in the paper "Acquisition of Localization Confidence for Accurate Object Detection" (https://arxiv.org/abs/1807.11590).
Pretrained ConvNets for pytorch: ResNeXt101, ResNet152, InceptionV4, InceptionResnetV2, etc.
PRML algorithms implemented in Python
Repository of notes, code and notebooks for the book Pattern Recognition and Machine Learning by Christopher Bishop
《机器学习》(西瓜书)公式推导解析,在线阅读地址:https://datawhalechina.github.io/pumpkin-book
:bar_chart: Benchmark multiple object trackers (MOT) in Python
Comprehensive Python Cheatsheet
The "Python Machine Learning (2nd edition)" book code repository and info resource
A short guide on features of Python 3
95.16% on CIFAR10 with PyTorch