7 papers
AG-VAS: Anchor-Guided Zero-Shot Visual Anomaly Segmentation with Large Multimodal Models
Zhen Qu, Xian Tao, Xiaoyi Bao +4
Large multimodal models (LMMs) exhibit strong task generalization capabilities, offering new opportunities for zero-shot visual anomaly segmentation (ZSAS). However, existing LMM-b…
ShowTable: Unlocking Creative Table Visualization with Collaborative Reflection and Refinement
Zhihang Liu, Xiaoyi Bao, Pandeng Li +7
While existing generation and unified models excel at general image generation, they struggle with tasks requiring deep reasoning, planning, and precise data-to-visual mapping abil…
UniLiP: Adapting CLIP for Unified Multimodal Understanding, Generation and Editing
Hao Tang, Chenwei Xie, Xiaoyi Bao +4
In this paper, we propose UniLIP, a unified framework that adapts CLIP for multimodal understanding, generation and editing. Although CLIP excels at understanding, it lacks reconst…
UFO: A Unified Approach to Fine-grained Visual Perception via Open-ended Language Interface
Hao Tang, Chenwei Xie, Haiyang Wang +5
Generalist models have achieved remarkable success in both language and vision-language tasks, showcasing the potential of unified modeling. However, effectively integrating fine-g…
DynImg: Key Frames with Visual Prompts are Good Representation for Multi-Modal Video Understanding
Xiaoyi Bao, Chenwei Xie, Hao Tang +4
In recent years, the introduction of Multi-modal Large Language Models (MLLMs) into video understanding tasks has become increasingly prevalent. However, how to effectively integra…
GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning
Xiaoyi Bao, Jindi Lv, Xiaofeng Wang +6
Recent progress in diffusion models has greatly enhanced video generation quality, yet these models still require fine-tuning to improve specific dimensions like instance preservat…