43 citations · 106 across the 11 of their papers we have counts for
13 papers · 1 filter
Memory-Free Generative Replay For Class-Incremental Learning
Xiaomeng Xin, Yiran Zhong, Yunzhong Hou +2
Regularization-based methods are beneficial to alleviate the catastrophic forgetting problem in class-incremental learning. With the absence of old task images, they often assume t…
Teacher-Student Asynchronous Learning with Multi-Source Consistency for Facial Landmark Detection
Rongye Meng, Sanping Zhou, Xingyu Wan +2
Due to the high annotation cost of large-scale facial landmark detection tasks in videos, a semi-supervised paradigm that uses self-training for mining high-quality pseudo-labels t…
End-to-End Multi-Object Tracking with Global Response Map
Xingyu Wan, Jiakai Cao, Sanping Zhou +1
Most existing Multi-Object Tracking (MOT) approaches follow the Tracking-by-Detection paradigm and the data association framework where objects are firstly detected and then associ…
STH: Spatio-Temporal Hybrid Convolution for Efficient Action Recognition
Xu Li, Jingwen Wang, Lin Ma +4
Effective and Efficient spatio-temporal modeling is essential for action recognition. Existing methods suffer from the trade-off between model performance and model complexity. In…
Multiple Object Tracking by Flowing and Fusing
Jimuyang Zhang, Sanping Zhou, Xin Chang +4
Most of Multiple Object Tracking (MOT) approaches compute individual target features for two subtasks: estimating target-wise motions and conducting pair-wise Re-Identification (Re…
Collaborative Attention Network for Person Re-identification
Wenpeng Li, Yongli Sun, Jinjun Wang +3
Jointly utilizing global and local features to improve model accuracy is becoming a popular approach for the person re-identification (ReID) problem, because previous works using g…