activity
20242026
most citedVisual Position Prompt for MLLM based Visual Grounding

1 citations · 1 across the 9 of their papers we have counts for

collaborators

12 papers

cs.CV2026

Diagram-MMU: A Multi-Modal Benchmark for Scientific Diagrams

Weihao Bo, Shan Zhang, Yanpeng Sun +7

Multimodal Large Language Models (MLLMs) have been growing the capability for scientific writing and collaboration. For example, OpenAI Prism is a free workspace for scientific wri…

cs.CV2025

Artemis: Structured Visual Reasoning for Perception Policy Learning

Wei Tang, Yanpeng Sun, Shan Zhang +6

Recent reinforcement-learning frameworks for visual perception policy usually incorporate intermediate reasoning chains expressed in natural language. Empirical observations indica…

cs.AI2025

Agentic Learner with Grow-and-Refine Multimodal Semantic Memory

Weihao Bo, Shan Zhang, Yanpeng Sun +9

MLLMs exhibit strong reasoning on isolated queries, yet they operate de novo -- solving each problem independently and often repeating the same mistakes. Existing memory-augmented…

cs.CV2025

FedMGP: Personalized Federated Learning with Multi-Group Text-Visual Prompts

Weihao Bo, Yanpeng Sun, Yu Wang +2

In this paper, we introduce FedMGP, a new paradigm for personalized federated prompt learning in vision-language models. FedMGP equips each client with multiple groups of paired te…

cs.CV2025★ 1 cited

Visual Position Prompt for MLLM based Visual Grounding

Wei Tang, Yanpeng Sun, Qinying Gu +1

Although Multimodal Large Language Models (MLLMs) excel at various image-related tasks, they encounter challenges in precisely aligning coordinates with spatial information within…

cs.CV2025

3CAD: A Large-Scale Real-World 3C Product Dataset for Unsupervised Anomaly

Enquan Yang, Peng Xing, Hanyang Sun +4

Industrial anomaly detection achieves progress thanks to datasets such as MVTec-AD and VisA. However, they suffer from limitations in terms of the number of defect samples, types o…

cs.CV2024

Enhancing Descriptive Captions with Visual Attributes for Multimodal Perception

Yanpeng Sun, Jing Hao, Ke Zhu +6

Training Large Multimodality Models (LMMs) relies on descriptive image caption that connects image and language. Existing methods for generating such captions often rely on distill…

cs.CV2024

Improving Multi-modal Large Language Model through Boosting Vision Capabilities

Yanpeng Sun, Huaxin Zhang, Qiang Chen +5

We focus on improving the visual understanding capability for boosting the vision-language models. We propose \textbf{Arcana}, a multiModal language model, which introduces two cru…

cs.CV2024

CSGO: Content-Style Composition in Text-to-Image Generation

Peng Xing, Haofan Wang, Yanpeng Sun +5

The diffusion model has shown exceptional capabilities in controlled image generation, which has further fueled interest in image style transfer. Existing works mainly focus on tra…

cs.CV2024

A Recover-then-Discriminate Framework for Robust Anomaly Detection

Peng Xing, Dong Zhang, Jinhui Tang +1

Anomaly detection (AD) has been extensively studied and applied in a wide range of scenarios in the recent past. However, there are still gaps between achieved and desirable levels…

cs.CV2024

Inv-Adapter: ID Customization Generation via Image Inversion and Lightweight Adapter

Peng Xing, Ning Wang, Jianbo Ouyang +1

The remarkable advancement in text-to-image generation models significantly boosts the research in ID customization generation. However, existing personalization methods cannot sim…

cs.CV2024

VRP-SAM: SAM with Visual Reference Prompt

Yanpeng Sun, Jiahui Chen, Shan Zhang +7

In this paper, we propose a novel Visual Reference Prompt (VRP) encoder that empowers the Segment Anything Model (SAM) to utilize annotated reference images as prompts for segmenta…