2 citations · 2 across the 1 of their papers we have counts for
5 papers · 1 filter
Multi-Task Learning via Co-Attentive Sharing for Pedestrian Attribute Recognition
Haitian Zeng, Haizhou Ai, Zijie Zhuang +1
Learning to predict multiple attributes of a pedestrian is a multi-task learning problem. To share feature representation between two individual task networks, conventional methods…
Rethinking the Distribution Gap of Person Re-identification with Camera-based Batch Normalization
Zijie Zhuang, Longhui Wei, Lingxi Xie +5
The fundamental difficulty in person re-identification (ReID) lies in learning the correspondence among individual cameras. It strongly demands costly inter-camera annotations, yet…
Learning Lightweight Pedestrian Detector with Hierarchical Knowledge Distillation
Rui Chen, Haizhou Ai, Chong Shang +2
It remains very challenging to build a pedestrian detection system for real world applications, which demand for both accuracy and speed. This work presents a novel hierarchical kn…
Cross-Resolution Person Re-identification with Deep Antithetical Learning
Zijie Zhuang, Haizhou Ai, Long Chen +1
Images with different resolutions are ubiquitous in public person re-identification (ReID) datasets and real-world scenes, it is thus crucial for a person ReID model to handle the…
Real-time Multiple People Tracking with Deeply Learned Candidate Selection and Person Re-Identification
Long Chen, Haizhou Ai, Zijie Zhuang +1
Online multi-object tracking is a fundamental problem in time-critical video analysis applications. A major challenge in the popular tracking-by-detection framework is how to assoc…