Person_reID_baseline_pytorch
Object ReID baseline
A PyTorch implementation of an Object Re-ID baseline with various training methods and architectures
Pytorch ReID: A tiny, friendly, strong pytorch implement of person re-id / vehicle re-id baseline. Tutorial 👉https://github.com/layumi/Person_reID_baseline_pytorch/tree/master/tutorial
4k stars
77 watching
1k forks
Language: Python
last commit: 5 months ago awesome-reidbaselinecircle-losscuhk-npimage-retrievalimage-searchmarket-1501metric-learningmsmt17object-reidopen-reidperson-reidperson-reidentificationpytorchrandom-erasingre-rankingtutorialvehicle-reid
Related projects:
Repository | Description | Stars |
---|---|---|
| A PyTorch library for training and retraining deep neural networks for person re-identification in images and videos. | 4,353 |
| An open-source person reidentification system using joint discriminative and generative learning. | 1,280 |
| Provides a PyTorch implementation of single image super-resolution | 2,457 |
| An implementation of a deep learning network for human pose estimation using high-resolution representations | 4,354 |
| An implementation of a deep learning-based object detection system in PyTorch. | 5,160 |
| A comprehensive library for training and applying deep learning models for image segmentation | 9,829 |
| A PyTorch implementation of a self-supervised learning method for learning robust visual features without supervision. | 9,425 |
| Pytorch implementation of unsupervised depth and ego-motion learning from video sequences | 1,022 |
| A PyTorch implementation of a deep learning model for 3D multi-person pose estimation from a single RGB image | 825 |
| A PyTorch implementation of a deep learning model for super resolution | 194 |
| An open source implementation of deep learning-based human segmentation models using PyTorch | 558 |
| Transfers pre-trained I3D network weights from TensorFlow to PyTorch | 532 |
| A comprehensive tutorial project that provides code examples for learning PyTorch by implementing various deep learning models and demonstrating their usage. | 30,401 |
| A Python framework for building deep learning models with optimized encoding layers and batch normalization. | 2,044 |
| An implementation of CloudWalk's DenseBody paper using PyTorch | 411 |