4 citations · 6 across the 10 of their papers we have counts for
12 papers · 1 filter
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…
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…
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…
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…
Aligned Better, Listen Better for Audio-Visual Large Language Models
Yuxin Guo, Shuailei Ma, Shijie Ma +7
Audio is essential for multimodal video understanding. On the one hand, video inherently contains audio, which supplies complementary information to vision. Besides, video large la…
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…
EgoVid-5M: A Large-Scale Video-Action Dataset for Egocentric Video Generation
Xiaofeng Wang, Kang Zhao, Feng Liu +6
Video generation has emerged as a promising tool for world simulation, leveraging visual data to replicate real-world environments. Within this context, egocentric video generation…
DriveDreamer-2: LLM-Enhanced World Models for Diverse Driving Video Generation
Guosheng Zhao, Xiaofeng Wang, Zheng Zhu +4
World models have demonstrated superiority in autonomous driving, particularly in the generation of multi-view driving videos. However, significant challenges still exist in genera…
CoReS: Orchestrating the Dance of Reasoning and Segmentation
Xiaoyi Bao, Siyang Sun, Shuailei Ma +5
The reasoning segmentation task, which demands a nuanced comprehension of intricate queries to accurately pinpoint object regions, is attracting increasing attention. However, Mult…
Relevant Intrinsic Feature Enhancement Network for Few-Shot Semantic Segmentation
Xiaoyi Bao, Jie Qin, Siyang Sun +2
For few-shot semantic segmentation, the primary task is to extract class-specific intrinsic information from limited labeled data. However, the semantic ambiguity and inter-class s…
Understanding the Multi-modal Prompts of the Pre-trained Vision-Language Model
Shuailei Ma, Chen-Wei Xie, Ying Wei +5
Prompt learning has emerged as an efficient alternative for fine-tuning foundational models, such as CLIP, for various downstream tasks. However, there is no work that provides a c…