AlvaHan

Pinned Repositories

3DDFA
The PyTorch improved version of TPAMI 2017 paper: Face Alignment in Full Pose Range: A 3D Total Solution.
Language:Python00
ai-edu
AI education materials for Chinese students, teachers and IT professionals.
Language:HTML00
aimet
AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.
Language:Python00
AlignPS
Code for CVPR 2021 paper: Anchor-Free Person Search
Language:Python00
Amend-Representation-Module
ARM - Official PyTorch Implementation
Language:Python00
awesome-CARLA
👉 CARLA resources such as tutorial, blog, code and etc https://github.com/carla-simulator/carla
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awesome-graph-classification
A collection of important graph embedding, classification and representation learning papers with implementations.
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ByteTrack
ByteTrack: Multi-Object Tracking by Associating Every Detection Box
Language:Python00
centroids-reid
On the Unreasonable Effectiveness of Centroids in Image Retrieval
Language:Python00
ReID_tutorial_slides
《深度学习与行人重识别》课程课件
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AlvaHan's Repositories

AlvaHan/aimet
AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.
Language:Python00
AlvaHan/AlignPS
Code for CVPR 2021 paper: Anchor-Free Person Search
Language:Python00
AlvaHan/ByteTrack
ByteTrack: Multi-Object Tracking by Associating Every Detection Box
Language:Python00
AlvaHan/centroids-reid
On the Unreasonable Effectiveness of Centroids in Image Retrieval
Language:Python00
AlvaHan/CVPR2022-Papers-with-Code
CVPR 2022 论文和开源项目合集
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AlvaHan/DanceTrack
DanceTrack: Multiple Object Tracking in Uniform Appearance and Diverse Motion, CVPR2022
AlvaHan/DeCLIP
Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm
AlvaHan/face-alignment
:fire: 2D and 3D Face alignment library build using pytorch
AlvaHan/FairMOT
[IJCV-2021] FairMOT: On the Fairness of Detection and Re-Identification in Multi-Object Tracking
AlvaHan/fast-reid
SOTA Re-identification Methods and Toolbox
AlvaHan/Former-DFER
“Former-DFER: Dynamic Facial Expression Recognition Transformer”, ACM MM 2021.
AlvaHan/GOSTnets
Convenience wrapper for networkx analysis using geospatial information, focusing on OSM
AlvaHan/handson-ml2
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
AlvaHan/ICON
ICON: Implicit Clothed humans Obtained from Normals (CVPR 2022)
AlvaHan/MAE-pytorch
Unofficial PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners
AlvaHan/mmsegmentation
OpenMMLab Semantic Segmentation Toolbox and Benchmark.
AlvaHan/nniefacelib
nniefacelib是一个在海思35xx系列芯片上运行的人脸算法库
AlvaHan/Person_reID_baseline_pytorch
Pytorch ReID: A tiny, friendly, strong pytorch implement of object re-identification baseline. Tutorial 👉https://github.com/layumi/Person_reID_baseline_pytorch/tree/master/tutorial
AlvaHan/pytorch-metric-learning
The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
AlvaHan/SegFormer
Official PyTorch implementation of SegFormer
AlvaHan/SeqNet
[AAAI 2021] Sequential End-to-end Network for Efficient Person Search
AlvaHan/SOD100K
The official repo of the TPAMI 2021/ECCV 2020 work CSNet: A Highly Efficient Model with 100K Parameters to Study the Semantics of Salient Object Detection
AlvaHan/SOTS
Single object tracking and segmentation.
AlvaHan/StrongSORT
StrongSORT: Make DeepSORT Great Again
AlvaHan/svox2
Plenoxels: Radiance Fields without Neural Networks, Code release WIP
AlvaHan/Swin-Transformer
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
AlvaHan/Towards-Realtime-MOT
Joint Detection and Embedding for fast multi-object tracking
AlvaHan/TrackEval
HOTA (and other) evaluation metrics for Multi-Object Tracking (MOT).
AlvaHan/TransReID
[ICCV-2021] TransReID: Transformer-based Object Re-Identification
AlvaHan/UniTrack
[NeurIPS'21] Unified tracking framework with a single appearance model. It supports Single Object Tracking (SOT), Video Object Segmentation (VOS), Multi-Object Tracking (MOT), Multi-Object Tracking and Segmentation (MOTS), Pose Tracking, Video Instance Segmentation (VIS), and class-agnostic MOT (e.g. TAO dataset).