18 citations · 19 across the 6 of their papers we have counts for
6 papers
Q-Ponder: A Unified Training Pipeline for Reasoning-based Visual Quality Assessment
Zhuoxuan Cai, Jian Zhang, Xinbin Yuan +7
Recent studies demonstrate that multimodal large language models (MLLMs) can proficiently evaluate visual quality through interpretable assessments. However, existing approaches ty…
Enhancing Visual Grounding for GUI Agents via Self-Evolutionary Reinforcement Learning
Xinbin Yuan, Jian Zhang, Kaixin Li +8
Graphical User Interface (GUI) agents have made substantial strides in understanding and executing user instructions across diverse platforms. Yet, grounding these instructions to…
Unsupervised Modality Adaptation with Text-to-Image Diffusion Models for Semantic Segmentation
Ruihao Xia, Yu Liang, Peng-Tao Jiang +4
Despite their success, unsupervised domain adaptation methods for semantic segmentation primarily focus on adaptation between image domains and do not utilize other abundant visual…
Empowering Segmentation Ability to Multi-modal Large Language Models
Yuqi Yang, Peng-Tao Jiang, Jing Wang +4
Multi-modal large language models (MLLMs) can understand image-language prompts and demonstrate impressive reasoning ability. In this paper, we extend MLLMs' output by empowering M…
Segment Anything is A Good Pseudo-label Generator for Weakly Supervised Semantic Segmentation
Peng-Tao Jiang, Yuqi Yang
Weakly supervised semantic segmentation with weak labels is a long-lived ill-posed problem. Mainstream methods mainly focus on improving the quality of pseudo labels. In this repor…
Looking Through the Glass: Neural Surface Reconstruction Against High Specular Reflections
Jiaxiong Qiu, Peng-Tao Jiang, Yifan Zhu +3
Neural implicit methods have achieved high-quality 3D object surfaces under slight specular highlights. However, high specular reflections (HSR) often appear in front of target obj…