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20202026
most citedSelf-Supervised Generative Adversarial Network for Depth Estimation in Laparoscopic Images

4 citations · 6 across the 8 of their papers we have counts for

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5 papers · 1 filter

cs.CV2026

SurgNarrator: A Generative Retrieval Framework for Surgical Video Understanding

Yuqing Feng, Jiawei Ma, Kevin Qinghong Lin +6

Surgical procedures unfold as structured and recurring clinical events, whose real-time understanding via intraoperative surgical videos is critical for intraoperative decision-mak…

cs.CV2026

SurgCUT3R: Surgical Scene-Aware Continuous Understanding of Temporal 3D Representation

Kaiyuan Xu, Fangzhou Hong, Daniel Elson +1

Reconstructing surgical scenes from monocular endoscopic video is critical for advancing robotic-assisted surgery. However, the application of state-of-the-art general-purpose reco…

cs.CV2024

Tracking Everything in Robotic-Assisted Surgery

Bohan Zhan, Wang Zhao, Yi Fang +5

Accurate tracking of tissues and instruments in videos is crucial for Robotic-Assisted Minimally Invasive Surgery (RAMIS), as it enables the robot to comprehend the surgical scene…

cs.CV2023

HabiCrowd: A High Performance Simulator for Crowd-Aware Visual Navigation

An Dinh Vuong, Toan Tien Nguyen, Minh Nhat VU +5

Visual navigation, a foundational aspect of Embodied AI (E-AI), has been significantly studied in the past few years. While many 3D simulators have been introduced to support visua…

cs.CV20211 cited

H-Net: Unsupervised Attention-based Stereo Depth Estimation Leveraging Epipolar Geometry

Baoru Huang, Jian-Qing Zheng, Stamatia Giannarou +1

Depth estimation from a stereo image pair has become one of the most explored applications in computer vision, with most of the previous methods relying on fully supervised learnin…