26 citations · 51 across the 3 of their papers we have counts for
6 papers
Adversarial Visual Robustness by Causal Intervention
Kaihua Tang, Mingyuan Tao, Hanwang Zhang
Adversarial training is the de facto most promising defense against adversarial examples. Yet, its passive nature inevitably prevents it from being immune to unknown attackers. To…
Distilling Causal Effect of Data in Class-Incremental Learning
Xinting Hu, Kaihua Tang, Chunyan Miao +2
We propose a causal framework to explain the catastrophic forgetting in Class-Incremental Learning (CIL) and then derive a novel distillation method that is orthogonal to the exist…
Counterfactual VQA: A Cause-Effect Look at Language Bias
Yulei Niu, Kaihua Tang, Hanwang Zhang +3
VQA models may tend to rely on language bias as a shortcut and thus fail to sufficiently learn the multi-modal knowledge from both vision and language. Recent debiasing methods pro…
Learning to Segment the Tail
Xinting Hu, Yi Jiang, Kaihua Tang +3
Real-world visual recognition requires handling the extreme sample imbalance in large-scale long-tailed data. We propose a "divide&conquer" strategy for the challenging LVIS task:…
Auto-Encoding Scene Graphs for Image Captioning
Xu Yang, Kaihua Tang, Hanwang Zhang +1
We propose Scene Graph Auto-Encoder (SGAE) that incorporates the language inductive bias into the encoder-decoder image captioning framework for more human-like captions. Intuitive…
Learning to Compose Dynamic Tree Structures for Visual Contexts
Kaihua Tang, Hanwang Zhang, Baoyuan Wu +2
We propose to compose dynamic tree structures that place the objects in an image into a visual context, helping visual reasoning tasks such as scene graph generation and visual Q&A…