4 papers
Two Causal Principles for Improving Visual Dialog
Jiaxin Qi, Yulei Niu, Jianqiang Huang +1
This paper unravels the design tricks adopted by us, the champion team MReaL-BDAI, for Visual Dialog Challenge 2019: two causal principles for improving Visual Dialog (VisDial). By…
Unbiased Scene Graph Generation from Biased Training
Kaihua Tang, Yulei Niu, Jianqiang Huang +2
Today's scene graph generation (SGG) task is still far from practical, mainly due to the severe training bias, e.g., collapsing diverse "human walk on / sit on / lay on beach" into…
Debiased Fine-Tuning for Vision-language Models by Prompt Regularization
Beier Zhu, Yulei Niu, Saeil Lee +2
We present a new paradigm for fine-tuning large-scale visionlanguage pre-trained models on downstream task, dubbed Prompt Regularization (ProReg). Different from traditional fine-t…
Prompt-aligned Gradient for Prompt Tuning
Beier Zhu, Yulei Niu, Yucheng Han +2
Thanks to the large pre-trained vision-language models (VLMs) like CLIP, we can craft a zero-shot classifier by "prompt", e.g., the confidence score of an image being "[CLASS]" can…