219 citations · 449 across the 20 of their papers we have counts for
27 papers
MT-GBM: A Multi-Task Gradient Boosting Machine with Shared Decision Trees
ZhenZhe Ying, Zhuoer Xu, Zhifeng Li +2
Despite the success of deep learning in computer vision and natural language processing, Gradient Boosted Decision Tree (GBDT) is yet one of the most powerful tools for application…
Regional Adversarial Training for Better Robust Generalization
Chuanbiao Song, Yanbo Fan, Yichen Yang +4
Adversarial training (AT) has been demonstrated as one of the most promising defense methods against various adversarial attacks. To our knowledge, existing AT-based methods usuall…
Target Adaptive Context Aggregation for Video Scene Graph Generation
Yao Teng, Limin Wang, Zhifeng Li +1
This paper deals with a challenging task of video scene graph generation (VidSGG), which could serve as a structured video representation for high-level understanding tasks. We pre…
UniFaceGAN: A Unified Framework for Temporally Consistent Facial Video Editing
Meng Cao, Haozhi Huang, Hao Wang +6
Recent research has witnessed advances in facial image editing tasks including face swapping and face reenactment. However, these methods are confined to dealing with one specific…
Structure-Regularized Attention for Deformable Object Representation
Shenao Zhang, Li Shen, Zhifeng Li +1
Capturing contextual dependencies has proven useful to improve the representational power of deep neural networks. Recent approaches that focus on modeling global context, such as…
Attacking Adversarial Attacks as A Defense
Boxi Wu, Heng Pan, Li Shen +6
It is well known that adversarial attacks can fool deep neural networks with imperceptible perturbations. Although adversarial training significantly improves model robustness, fai…