Person Re-Identification
505 papers with code • 33 benchmarks • 56 datasets
Person Re-Identification is a computer vision task in which the goal is to match a person's identity across different cameras or locations in a video or image sequence. It involves detecting and tracking a person and then using features such as appearance, body shape, and clothing to match their identity in different frames. The goal is to associate the same person across multiple non-overlapping camera views in a robust and efficient manner.
Libraries
Use these libraries to find Person Re-Identification models and implementationsSubtasks
- Unsupervised Person Re-Identification
- Video-Based Person Re-Identification
- Generalizable Person Re-identification
- Cloth-Changing Person Re-Identification
- Cloth-Changing Person Re-Identification
- Large-Scale Person Re-Identification
- Cross-Modal Person Re-Identification
- Self-Supervised Person Re-Identification
- Clothes Changing Person Re-Identification
- Image-To-Video Person Re-Identification
- Semi-Supervised Person Re-Identification
- Direct Transfer Person Re-identification
- Federated Lifelong Person ReID
Latest papers
Camera-aware Label Refinement for Unsupervised Person Re-identification
Unsupervised person re-identification aims to retrieve images of a specified person without identity labels.
View-decoupled Transformer for Person Re-identification under Aerial-ground Camera Network
Experiments on two datasets show that VDT is a feasible and effective solution for AGPReID, surpassing the previous method on mAP/Rank1 by up to 5. 0%/2. 7% on CARGO and 3. 7%/5. 2% on AG-ReID, keeping the same magnitude of computational complexity.
Implicit Discriminative Knowledge Learning for Visible-Infrared Person Re-Identification
To address this issue, we propose a novel Implicit Discriminative Knowledge Learning (IDKL) network to uncover and leverage the implicit discriminative information contained within the modality-specific.
A Versatile Framework for Multi-scene Person Re-identification
To overcome significant variations between images across camera views, mountains of variants of ReID models were developed for solving a number of challenges, such as resolution change, clothing change, occlusion, modality change, and so on.
Occluded Cloth-Changing Person Re-Identification
We define cloth-changing person re-identification in occlusion scenarios as occluded cloth-changing person re-identification (Occ-CC-ReID), and to the best of our knowledge, we are the first to propose occluded cloth-changing person re-identification as a new task.
YYDS: Visible-Infrared Person Re-Identification with Coarse Descriptions
To this end, we present the Refer-VI-ReID settings, which aims to match target visible images from both infrared images and coarse language descriptions (e. g., "a man with red top and black pants") to complement the missing color information.
GAF-Net: Video-Based Person Re-Identification via Appearance and Gait Recognitions
These features are then combined into a single feature allowing the re-identification of individuals.
Source-Guided Similarity Preservation for Online Person Re-Identification
Our framework is based on the extraction of a support set composed of source images that maximizes the similarity with the target data.
DROP: Decouple Re-Identification and Human Parsing with Task-specific Features for Occluded Person Re-identification
Unlike mainstream approaches using global features for simultaneous multi-task learning of ReID and human parsing, or relying on semantic information for attention guidance, DROP argues that the inferior performance of the former is due to distinct granularity requirements for ReID and human parsing features.
A Survey on 3D Skeleton Based Person Re-Identification: Approaches, Designs, Challenges, and Future Directions
Person re-identification via 3D skeletons is an important emerging research area that triggers great interest in the pattern recognition community.