arXiv AI

Surg-UniWorld: A Unified Surgical World Model with Multimodal Control Experts

arXiv:2608. 06770v1 Announce Type: new Abstract: Controllable surgical world models can provide a generative foundation for surgical artificial intelligence and simulation by synthesizing realistic instrument--tissue interactions.

arXiv Computer Vision

Aug 28

Surgical Video Generation From Diffusion to World Models: A Survey

This survey reviews recent advances in surgical video generation, categorizing methods into unconditional, conditional, and world modeling generation. It highlights a shift from creating visually plausible frames to modeling the causal dynamics of surgical scenes, and discusses challenges such as pixel-level fidelity versus clinical plausibility, generalization, physical realism, controllability, and interpretability. The paper also compiles experimental results from public datasets to serve as a quantitative benchmark for the field.

By Fuxiang Huang, Chenxu Zhang, Liang Han, Lei Zhang

diffusion robotics multimodal safety

arXiv Computer Vision

Sep 22

SurgMotion: A Video-Native Foundation Model for Universal Understanding of Surgical Videos

SurgMotion is a video-native foundation model that replaces pixel-level reconstruction with latent motion prediction for surgical video analysis. It introduces motion-guided masked prediction, spatiotemporal affinity self-distillation, and spatiotemporal feature diversity regularization to focus on semantically meaningful regions and avoid representation collapse. Trained on SurgMotion-15M, the largest surgical video dataset, it outperforms state-of-the-art methods across 17 benchmarks, improving workflow recognition, action triplet recognition, skill assessment, polyp segmentation, and depth estimation.

By Jinlin Wu, Felix Holm, Chuxi Chen, An Wang, Yaxin Hu, Xiaofan Ye, Zelin Zang, Miao Xu, Lihua Zhou, Huai Liao, Danny T. M. Chan, Ming Feng, Wai S. Poon, Hongliang Ren, Dong Yi, Nassir Navab, Gaofeng Meng, Jiebo Luo, Hongbin Liu, Zhen Lei

rag computer-vision efficiency benchmarks

arXiv AI

Aug 12

Surgical WAM: A World-Action Model for Data-Efficient Surgical Robot Learning

arXiv:2608. 11204v1 Announce Type: cross Abstract: Learning reliable surgical manipulation policies is bottlenecked by the scarcity of action-labeled demonstrations: teleoperated surgical robot (e.

By Wenrui Bao, Tianyun Jiang, Zhiben Chen, Ser-Nam Lim, Peter D. Peng, Yuzhang Shang

robotics fine-tuning

arXiv Computer Vision

Aug 25

From Articulated Kinematics to Routed Visual Control for Action-Conditioned Surgical Video Generation

arXiv:2605.08712v2 Announce Type: replace Abstract: Action-conditioned surgical video generation is a critical yet highly challenging problem for robotic surgery. The core difficulty is that low-dime...

By Bohan Li, Shuojue Yang, Baorui Peng, Xianda Guo, Erli Zhang, Youqi Tao, Junfeng Duan, Daguang Xu, Qi Dou, Xin Jin, Wenjun Zeng, Hao Zhao, Yueming Jin

diffusion robotics efficiency benchmarks

arXiv Computer Vision

Aug 21

Towards Surgical World-Action Modeling: A Preliminary Joint Visual-Trajectory Forecasting for Surgical Motion Planning

arXiv:2608. 20284v1 Announce Type: new Abstract: Reliable surgical planning requires models to anticipate not only how instruments will move, but also how the operative visual state will evolve together with such motion.

By Weiliang Huang, Huanrong Liu, Bob Zhang, Qi Dou, Zhen Chen, Yun Gu, Guy Rosman, Qingbiao Li

arXiv Computer Vision

Aug 25

Dense Structural Priors for Sparse Functional Landmark Localization in Surgical Videos

The paper presents a method for localizing functional surgical landmarks—specifically instrument tips and anchors—in surgical videos without requiring manual pixel-level mask annotations. It leverages vision foundation models, such as SAM 3, to generate dense structural priors through zero‑shot, point‑prompted masks, and refines landmark predictions with a lightweight, coarse‑to‑fine multi‑frame network. Experiments on 7,867 clips from 60 videos show that the approach achieves F1 scores of 72.4% for tip and 58.0% for anchor localization, with ablations confirming the benefits of structural priors and refinement stages.

By Chenyan Jing, Hao Ding, Lalithkumar Seenivasan, Jacob M. Delgado L\'opez, Mathias Unberath

computer-vision robotics

arXiv AI

Aug 11

SurgLAT: Surgical Latent Attention Tracking for Depth-Aware Robotic Laparoscope Control

arXiv:2608. 07876v1 Announce Type: new Abstract: Autonomous laparoscopic camera control requires continuous understanding of the surgeon's operative intent in dynamic surgical scenes, where the target operative region is not a stable physical object but a latent and temporally evolving attention state.

By Rulin Zhou, Qiujie Song, Yujie Ma, An Wang, Wanhao Liu, Guoheng Ma, Yidu Wang, Guankun Wang, Xingrong Diao, Jiankun Wang, Chaowei Zhu, Xianming Liu, Hongliang Ren

agents robotics

Hugging Face Trending Papers

Sep 21

Colon3R: Cross-Domain 3D Reconstruction from Monocular Colonoscopic Video

Monocular colonoscopic 3D reconstruction is important for surgical robotic colonoscopy, but remains challenging due to weak texture, specular reflections, limited view overlap, and non-rigid tissue mo...

computer-vision robotics fine-tuning benchmarks

arXiv Computer Vision

Aug 25

SurgTEMP: Temporal-Aware Surgical Video Question Answering with Text-guided Visual Memory for Laparoscopic Cholecystectomy

arXiv:2603.29962v4 Announce Type: replace Abstract: Surgical procedures are inherently complex and risky, requiring extensive expertise and constant focus to navigate evolving intraoperative scenes....

By Shi Li, Vinkle Srivastav, Nicolas Chanel, Saurav Sharma, Nabani Banik, Lorenzo Arboit, Kun Yuan, Pietro Mascagni, Nicolas Padoy

llms nlp fine-tuning multimodal benchmarks safety

arXiv AI

Aug 24

Action-grounded tissue affordance enables anticipatory auto-framing that lowers surgeon cognitive workload during laparoscopic surgery

arXiv:2608.02471v2 Announce Type: replace-cross Abstract: In laparoscopy, surgeon gaze tracks where the instruments will act; easing this demand through visual attention modeling requires dense label...

By Jiayu Gu, Yiwei Wang, Jie Zhang, Guojun Cao, Keshen Lyu, Song Zhou, Yimeng Chen, Haorui Wang, Qingmin Feng, Shenchao Shi, Hongkuan Shi, Qiuyu Yu, Qiang Xie, Huan Zhao, Wenbin Chen, Caihua Xiong, Chidan Wan, Jing Samantha Pan, Xiong Cai, Han Ding

arXiv AI

Jun 6

Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics

arXiv:2604. 21017v3 Announce Type: replace-cross Abstract: Autonomous medical robots hold promise to improve patient outcomes, reduce provider workload, democratize access to care, and enable superhuman precision.

By Open-H-Embodiment Consortium, :, Nigel Nelson, Juo-Tung Chen, Jesse Haworth, Xinhao Chen, Lukas Zbinden, Dianye Huang, Alaa Eldin Abdelaal, Alberto Arezzo, Ayberk Acar, Farshid Alambeigi, Carlo Alberto Ammirati, Yunke Ao, Pablo David Aranda Rodriguez, Soofiyan Atar, Mattia Ballo, Noah Barnes, Federica Barontini, Filip Binkiewicz, Peter Black, Sebastian Bodenstedt, Leonardo Borgioli, Nikola Budjak, Benjamin Calm\'e, Fabio Carrillo, Nicola Cavalcanti, Changwei Chen, Haoxin Chen, Sihang Chen, Qihan Chen, Zhongyu Chen, Ziyang Chen, Shing Shin Cheng, Meiqing Cheng, Min Cheng, Zih-Yun Sarah Chiu, Xiangyu Chu, Camilo Correa-Gallego, Giulio Dagnino, Anton Deguet, Jacob Delgado, Jonathan C. DeLong, Kaizhong Deng, Alexander Dimitrakakis, Qingpeng Ding, Hao Ding, Giovanni Distefano, Daniel Donoho, Anqing Duan, Marco Esposito, Shane Farritor, Jad Fayad, Zahi Fayad, Mario Ferradosa, Filippo Filicori, Chelsea Finn, Philipp F\"urnstahl, Jiawei Ge, Stamatia Giannarou, Xavier Giralt Ludevid, Frederic Giraud, Aditya Amit Godbole, Ken Goldberg, Antony Goldenberg, Diego Granero Marana, Xiaoqing Guo, Tam\'as Haidegger, Evan Hailey, Pascal Hansen, Ziyi Hao, Kush Hari, Kengo Hayashi, Jonathon Hawkins, Shelby Haworth, Ortrun Hellig, S. Duke Herrell, Zhouyang Hong, Andrew Howe, Junlei Hu, Zhaoyang Jacopo Hu, Ria Jain, Mohammad Rafiee Javazm, Howard Ji, Rui Ji, Jianmin Ji, Zhongliang Jiang, Dominic Jones, Jeffrey Jopling, Britton Jordan, Ran Ju, Michael Kam, Luoyao Kang, Fausto Kang, Siddhartha Kapuria, Peter Kazanzides, Sonika Kiehler, Ethan Kilmer, Ji Woong Kim, Przemys{\l}aw Korzeniowski, Chandra Kuchi, Nithesh Kumar, Alan Kuntz, Federico Lavagno, Yu Chung Lee, Hao-Chih Lee, Hang Li, Zhen Li, Xiao Liang, Xinxin Lin, Jinsong Lin, Chang Liu, Fei Liu, Pei Liu, Yun-hui Liu, Wanli Liuchen, Eszter Luk\'acs, Sareena Mann, Miles Mannas, Brett Marinelli, Sabina Martyniak, Francesco Marzola, Lorenzo Mazza, Xueyan Mei, Maria Clara Morais, Luigi Muratore, Chetan Reddy Narayanaswamy, Micha{\l} Naskr\k{e}t, David Navarro-Alarcon, Cyrus Neary, Chi Kit Ng, Christopher Nguan, David Noonan, Ki Hwan Oh, Tom Christian Olesch, Allison M. Okamura, Justin Opfermann, Matteo Pescio, Doan Xuan Viet Pham, Tito Porras, Hongliang Ren, Ariel Rodriguez Jimenez, Ferdinando Rodriguez y Baena, Septimiu E. Salcudean, Asmitha Sathya, Preethi Satish, Lalithkumar Seenivasan, Jiaqi Shao, Yiqing Shen, Yu Sheng, Lucy XiaoYang Shi, Zoe Soul\'e, Stefanie Speidel, Mingwu Su, Jianhao Su, Idris Sunmola, Krist\'of Tak\'acs, Yunxi Tang, Patrick Thornycroft, Yu Tian, Jordan Thompson, Mehmet K. Turkcan, Mathias Unberath, Pietro Valdastri, Carlos Vives, Quan Vuong, Martin Wagner, Farong Wang, Wei Wang, Lidian Wang, Chung-Pang Wang, Guankun Wang, Junyi Wang, Erqi Wang, Ziyi Wang, Tanner Watts, Wolfgang Wein, Yimeng Wu, Zijian Wu, Hongjun Wu, Luohong Wu, Jie Ying Wu, Junlin Wu, Victoria Wu, Kaixuan Wu, Mateusz W\'ojcikowski, Yunye Xiao, Nan Xiao, Wenxuan Xie, Hao Yang, Tianqi Yang, Yinuo Yang, Menglong Ye, Ryan S. Yeung, Nural Yilmaz, Chim Ho Yin, Michael Yip, Rayan Younis, Chenhao Yu, Sayem Nazmuz Zaman, Milos Zefran, Han Zhang, Yuelin Zhang, Yidong Zhang, Yanyong Zhang, Xuyang Zhang, Yameng Zhang, Joyce Zhang, Ning Zhong, Peng Zhou, Haoying Zhou, Xiuli Zuo, Nassir Navab, Mahdi Azizian, Sean D. Huver, Axel Krieger

agents robotics multimodal benchmarks

arXiv AI

Jun 30

SurgVLA-Bench: Towards Evaluating Vision-Language-Action Models for Laparoscopic Surgical Robotics

arXiv:2606. 29247v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models represent a promising direction for embodied intelligence in surgical robotics.

By Jiashuo Sun, Yue He, Wenxuan Liu, Tao Mao, Jiazheng Wang, Xiang Chen, Min Liu

diffusion robotics multimodal benchmarks

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