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This project is a PyTorch person re-identification framework designed for training and evaluating models that identify individuals across different camera views. It provides a complete model training pipeline, a deep learning feature extractor for converting images into numeric vectors, and a suite of computer vision benchmarking tools to measure identity retrieval accuracy. The framework includes a specialized transfer learning toolkit that supports layer freezing, staged learning rate optimization, and differential learning rates for fine-tuning pretrained models. It distinguishes itself th
This project is a comprehensive library for transfer learning and domain adaptation in computer vision. It serves as a framework for aligning feature distributions between source and target datasets, a toolkit for domain generalization, and a library for semi-supervised learning using small labeled datasets and large unlabeled sets. The library provides specialized capabilities for unsupervised domain adaptation, including the use of adversarial networks, discrepancy-based architectures, and image-to-image translation to reduce distribution mismatch. It also includes tools for domain generali
DeepSORT is a real-time multi-object tracking framework designed to maintain consistent identities of multiple objects across video frames. It integrates deep learning appearance features with motion descriptors to track objects through a sequence of video data. The system uses a deep convolutional neural network to generate high-dimensional visual descriptors for person re-identification. These appearance features are combined with motion estimation via Kalman filtering and solved using the Hungarian algorithm to optimally associate detections with existing tracks. The framework includes ca
ICLR-2020 Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification.
Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-identification (ICCV 2019, Oral)
The main features of oasisyang/ssg are: Person Re-identification.
Projects with overlapping indexed features include: kaiyangzhou/deep-person-reid — This project is a PyTorch person re-identification framework designed for training and evaluating models that identify… thuml/transfer-learning-library — This project is a comprehensive library for transfer learning and domain adaptation in computer vision. It serves as a… nwojke/deep_sort — DeepSORT is a real-time multi-object tracking framework designed to maintain consistent identities of multiple objects… yxgeee/mmt — [ICLR-2020] Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification. helioszhao/m3l — Pytorch implementation for M^3L. CVPR 2021. zhunzhong07/ecn — Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identification CVPR 2019.