activity
20242026
most citedSAM 2 in Robotic Surgery: An Empirical Evaluation for Robustness and Generalization in Surgical Video Segmentation

2 citations · 4 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CV2026

Generative World Simulation with DAO and JING

XGEN Team, Guohao Cai, Haoxuan Che +16

We present a Generative World Simulation framework that couples persistent shared world state with continuous first-person audiovisual generation. The framework integrates DAO, a c…

cs.CV2026

CM-EVS: Sparse Panoramic RGB-D-Pose Data for Complete Scene Coverage

Jiale Liu, Jungang Li, Jieming Yu +17

Modern 3D visual learning relies on observations sampled from metric 3D assets, yet existing scans, meshes, point clouds, simulations, and reconstructions do not directly provide a…

cs.CV2026

DINOv3 Beats Specialized Detectors: A Simple Foundation Model Baseline for Image Forensics

Jieming Yu, Qiuxiao Feng, Zhuohan Wang +1

With the rapid advancement of deep generative models, realistic fake images have become increasingly accessible, yet existing localization methods rely on complex designs and still…

cs.CV2025

More than Segmentation: Benchmarking SAM 3 for Segmentation, 3D Perception, and Reconstruction in Robotic Surgery

Wenzhen Dong, Jieming Yu, Yiming Huang +5

The recent SAM 3 and SAM 3D have introduced significant advancements over the predecessor, SAM 2, particularly with the integration of language-based segmentation and enhanced 3D p…

cs.CV2025★ 1 cited

Does DINOv3 Set a New Medical Vision Standard? Benchmarking 2D and 3D Classification, Segmentation, and Registration

Che Liu, Yinda Chen, Haoyuan Shi +21

The advent of large-scale vision foundation models, pre-trained on diverse natural images, has marked a paradigm shift in computer vision. However, how the frontier vision foundati…

cs.CV2024★ 2 cited

SAM 2 in Robotic Surgery: An Empirical Evaluation for Robustness and Generalization in Surgical Video Segmentation

Jieming Yu, An Wang, Wenzhen Dong +5

The recent Segment Anything Model (SAM) 2 has demonstrated remarkable foundational competence in semantic segmentation, with its memory mechanism and mask decoder further addressin…

eess.IV2024★ 1 cited

Adapting SAM for Surgical Instrument Tracking and Segmentation in Endoscopic Submucosal Dissection Videos

Jieming Yu, Long Bai, Guankun Wang +4

The precise tracking and segmentation of surgical instruments have led to a remarkable enhancement in the efficiency of surgical procedures. However, the challenge lies in achievin…