Fine-Grained Fusion With Distractor Suppression for Video-Based Person Re-Identification
Video based person re-identification aims to associate video clips with the same identity by designing discriminative and representative features. Existing approaches simply compute representations for video clips via frame-level or region-level feature aggregation, where fine-grained local informat...
Main Authors: | Jiali Xi, Qin Zhou, Yiru Zhao, Shibao Zheng |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2019-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8782110/ |
Similar Items
-
Video-based Person re-identification with parallel correction and fusion of pedestrian area features
by: Liang She, et al.
Published: (2023-01-01) -
Unsupervised Person Re-Identification with Attention-Guided Fine-Grained Features and Symmetric Contrast Learning
by: Yongzhi Wu, et al.
Published: (2022-09-01) -
Fusion schemes for image-to-video person re-identification
by: Thuy-Binh Nguyen, et al.
Published: (2019-01-01) -
Joint Multiple Fine-grained feature for Vehicle Re-Identification
by: Yan Xu, et al.
Published: (2022-07-01) -
Pose‐guided adversarial video prediction for image‐to‐video person re‐identification
by: Yunqi He, et al.
Published: (2023-12-01)