32 citations · 81 across the 34 of their papers we have counts for
5 papers · 1 filter
OphCLIP: Hierarchical Retrieval-Augmented Learning for Ophthalmic Surgical Video-Language Pretraining
Ming Hu, Kun Yuan, Yaling Shen +17
Surgical practice involves complex visual interpretation, procedural skills, and advanced medical knowledge, making surgical vision-language pretraining (VLP) particularly challeng…
Procedure-Aware Surgical Video-language Pretraining with Hierarchical Knowledge Augmentation
Kun Yuan, Vinkle Srivastav, Nassir Navab +1
Surgical video-language pretraining (VLP) faces unique challenges due to the knowledge domain gap and the scarcity of multi-modal data. This study aims to bridge the gap by address…
HecVL: Hierarchical Video-Language Pretraining for Zero-shot Surgical Phase Recognition
Kun Yuan, Vinkle Srivastav, Nassir Navab +1
Natural language could play an important role in developing generalist surgical models by providing a broad source of supervision from raw texts. This flexible form of supervision…
SelfPose3d: Self-Supervised Multi-Person Multi-View 3d Pose Estimation
Vinkle Srivastav, Keqi Chen, Nicolas Padoy
We present a new self-supervised approach, SelfPose3d, for estimating 3d poses of multiple persons from multiple camera views. Unlike current state-of-the-art fully-supervised meth…
Overcoming Dimensional Collapse in Self-supervised Contrastive Learning for Medical Image Segmentation
Jamshid Hassanpour, Vinkle Srivastav, Didier Mutter +1
Self-supervised learning (SSL) approaches have achieved great success when the amount of labeled data is limited. Within SSL, models learn robust feature representations by solving…