26 citations · 55 across the 4 of their papers we have counts for
6 papers
Causal Attention for Vision-Language Tasks
Xu Yang, Hanwang Zhang, Guojun Qi +1
We present a novel attention mechanism: Causal Attention (CATT), to remove the ever-elusive confounding effect in existing attention-based vision-language models. This effect cause…
Finding It at Another Side: A Viewpoint-Adapted Matching Encoder for Change Captioning
Xiangxi Shi, Xu Yang, Jiuxiang Gu +2
Change Captioning is a task that aims to describe the difference between images with natural language. Most existing methods treat this problem as a difference judgment without the…
Learning to Collocate Neural Modules for Image Captioning
Xu Yang, Hanwang Zhang, Jianfei Cai
We do not speak word by word from scratch; our brain quickly structures a pattern like \textsc{sth do sth at someplace} and then fill in the detailed descriptions. To render existi…
Unpaired Image Captioning via Scene Graph Alignments
Jiuxiang Gu, Shafiq Joty, Jianfei Cai +3
Most of current image captioning models heavily rely on paired image-caption datasets. However, getting large scale image-caption paired data is labor-intensive and time-consuming.…
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…
Shuffle-Then-Assemble: Learning Object-Agnostic Visual Relationship Features
Xu Yang, Hanwang Zhang, Jianfei Cai
Due to the fact that it is prohibitively expensive to completely annotate visual relationships, i.e., the (obj1, rel, obj2) triplets, relationship models are inevitably biased to o…