Person Re-identification in the Wild
Liang Zheng, Hengheng Zhang, Shaoyan Sun, Manmohan Chandraker, Yi, Yang, Qi Tian

TL;DR
This paper introduces a new large-scale dataset for person re-identification in videos, evaluates various detection and recognition methods, and proposes improvements to enhance re-identification accuracy.
Contribution
The paper presents the PRW dataset, analyzes the impact of detection on re-identification, and introduces an ID-discriminative embedding and confidence-weighted similarity for better performance.
Findings
Detection improves re-identification accuracy.
CNN-based embeddings enhance identification.
Detection scores can be effectively integrated into similarity measures.
Abstract
We present a novel large-scale dataset and comprehensive baselines for end-to-end pedestrian detection and person recognition in raw video frames. Our baselines address three issues: the performance of various combinations of detectors and recognizers, mechanisms for pedestrian detection to help improve overall re-identification accuracy and assessing the effectiveness of different detectors for re-identification. We make three distinct contributions. First, a new dataset, PRW, is introduced to evaluate Person Re-identification in the Wild, using videos acquired through six synchronized cameras. It contains 932 identities and 11,816 frames in which pedestrians are annotated with their bounding box positions and identities. Extensive benchmarking results are presented on this dataset. Second, we show that pedestrian detection aids re-identification through two simple yet effective…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsVideo Surveillance and Tracking Methods · Advanced Neural Network Applications · Fire Detection and Safety Systems
