584 citations · 1.2k across the 68 of their papers we have counts for
17 papers · 1 filter
A Strong Baseline for Semi-Supervised Incremental Few-Shot Learning
Linglan Zhao, Dashan Guo, Yunlu Xu +5
Few-shot learning (FSL) aims to learn models that generalize to novel classes with limited training samples. Recent works advance FSL towards a scenario where unlabeled examples ar…
Hindsight Reward Tweaking via Conditional Deep Reinforcement Learning
Ning Wei, Jiahua Liang, Di Xie +1
Designing optimal reward functions has been desired but extremely difficult in reinforcement learning (RL). When it comes to modern complex tasks, sophisticated reward functions ar…
TransForensics: Image Forgery Localization with Dense Self-Attention
Jing Hao, Zhixin Zhang, Shicai Yang +2
Nowadays advanced image editing tools and technical skills produce tampered images more realistically, which can easily evade image forensic systems and make authenticity verificat…
Self-Supervised Regional and Temporal Auxiliary Tasks for Facial Action Unit Recognition
Jingwei Yan, Jingjing Wang, Qiang Li +2
Automatic facial action unit (AU) recognition is a challenging task due to the scarcity of manual annotations. To alleviate this problem, a large amount of efforts has been dedicat…
Divide-and-Assemble: Learning Block-wise Memory for Unsupervised Anomaly Detection
Jinlei Hou, Yingying Zhang, Qiaoyong Zhong +3
Reconstruction-based methods play an important role in unsupervised anomaly detection in images. Ideally, we expect a perfect reconstruction for normal samples and poor reconstruct…
InsPose: Instance-Aware Networks for Single-Stage Multi-Person Pose Estimation
Dahu Shi, Xing Wei, Xiaodong Yu +3
Multi-person pose estimation is an attractive and challenging task. Existing methods are mostly based on two-stage frameworks, which include top-down and bottom-up methods. Two-sta…