5 citations · 9 across the 8 of their papers we have counts for
5 papers · 1 filter
Game2Real-Bench: Do Toy Games Reveal and Transfer to Real-World Visual Reasoning?
Qingan Liu, Juntong Feng, Yue Zhu +6
Visual reasoning is an important capability for vision-language models (VLMs) to understand visual evidence, spatial structure, constraints, and state changes. Existing evaluations…
VISTA-Bench: Do Vision-Language Models Really Understand Visualized Text as Well as Pure Text?
Qing'an Liu, Juntong Feng, Yuhao Wang +6
Vision-Language Models (VLMs) have achieved impressive performance in cross-modal understanding across textual and visual inputs, yet existing benchmarks predominantly focus on pur…
Stable Attribute Group Editing for Reliable Few-shot Image Generation
Guanqi Ding, Xinzhe Han, Shuhui Wang +3
Few-shot image generation aims to generate data of an unseen category based on only a few samples. Apart from basic content generation, a bunch of downstream applications hopefully…
Attribute Group Editing for Reliable Few-shot Image Generation
Guanqi Ding, Xinzhe Han, Shuhui Wang +4
Few-shot image generation is a challenging task even using the state-of-the-art Generative Adversarial Networks (GANs). Due to the unstable GAN training process and the limited tra…
Greedy Gradient Ensemble for Robust Visual Question Answering
Xinzhe Han, Shuhui Wang, Chi Su +2
Language bias is a critical issue in Visual Question Answering (VQA), where models often exploit dataset biases for the final decision without considering the image information. As…