13 citations · 33 across the 5 of their papers we have counts for
8 papers
Video Super-resolution with Temporal Group Attention
Takashi Isobe, Songjiang Li, Xu Jia +6
Video super-resolution, which aims at producing a high-resolution video from its corresponding low-resolution version, has recently drawn increasing attention. In this work, we pro…
CycAs: Self-supervised Cycle Association for Learning Re-identifiable Descriptions
Zhongdao Wang, Jingwei Zhang, Liang Zheng +4
This paper proposes a self-supervised learning method for the person re-identification (re-ID) problem, where existing unsupervised methods usually rely on pseudo labels, such as t…
Softmax Dissection: Towards Understanding Intra- and Inter-class Objective for Embedding Learning
Lanqing He, Zhongdao Wang, Yali Li +1
The softmax loss and its variants are widely used as objectives for embedding learning, especially in applications like face recognition. However, the intra- and inter-class object…
CS-R-FCN: Cross-supervised Learning for Large-Scale Object Detection
Ye Guo, Yali Li, Shengjin Wang
Generic object detection is one of the most fundamental problems in computer vision, yet it is difficult to provide all the bounding-box-level annotations aiming at large-scale obj…
HAR-Net: Joint Learning of Hybrid Attention for Single-stage Object Detection
Ya-Li Li, Shengjin Wang
Object detection has been a challenging task in computer vision. Although significant progress has been made in object detection with deep neural networks, the attention mechanism…
Perceive Where to Focus: Learning Visibility-aware Part-level Features for Partial Person Re-identification
Yifan Sun, Qin Xu, Yali Li +4
This paper considers a realistic problem in person re-identification (re-ID) task, i.e., partial re-ID. Under partial re-ID scenario, the images may contain a partial observation o…