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20232026
most citedEndoChat: Grounded Multimodal Large Language Model for Endoscopic Surgery

3 citations · 9 across the 37 of their papers we have counts for

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33 papers · 1 filter

cs.CV2026

UniDA3D: A Unified Domain-Adaptive Framework for Multi-View 3D Object Detection

Hongjing Wu, Cheng Chi, Jinlin Wu +3

Camera-only 3D object detection is critical for autonomous driving, offering a cost-effective alternative to LiDAR based methods. In particular, multi-view 3D object detection has…

cs.CV2025

Anatomy-R1: Enhancing Anatomy Reasoning in Multimodal Large Language Models via Anatomical Similarity Curriculum and Group Diversity Augmentation

Ziyang Song, Zelin Zang, Zuyao Chen +6

Multimodal Large Language Models (MLLMs) have achieved impressive progress in natural image reasoning, yet their potential in medical imaging remains underexplored, especially in c…

cs.CV2025

6DAttack: Backdoor Attacks in the 6DoF Pose Estimation

Jihui Guo, Zongmin Zhang, Zhen Sun +4

Deep learning advances have enabled accurate six-degree-of-freedom (6DoF) object pose estimation, widely used in robotics, AR/VR, and autonomous systems. However, backdoor attacks…

cs.CV2025

NeuroABench: A Multimodal Evaluation Benchmark for Neurosurgical Anatomy Identification

Ziyang Song, Zelin Zang, Xiaofan Ye +7

Multimodal Large Language Models (MLLMs) have shown significant potential in surgical video understanding. With improved zero-shot performance and more effective human-machine inte…

cs.CV2025

How Far Are Surgeons from Surgical World Models? A Pilot Study on Zero-shot Surgical Video Generation with Expert Assessment

Zhen Chen, Qing Xu, Jinlin Wu +7

Foundation models in video generation are demonstrating remarkable capabilities as potential world models for simulating the physical world. However, their application in high-stak…

cs.CV2025

Learning to Think Fast and Slow for Visual Language Models

Chenyu Lin, Cheng Chi, Jinlin Wu +2

When faced with complex problems, we tend to engage in slower, more deliberate thinking. In contrast, for simple questions we give quick, intuitive responses. This dual-system thin…