3 citations · 5 across the 7 of their papers we have counts for
5 papers · 1 filter
MeshFM: 2D Features Are All You Need for 3D Shape Understanding
Jinfan Zhou, Richard Liu, Itai Lang +1
We present MeshFM, an efficient feedforward framework for extracting rich features from 3D inputs. Our method distills 2D features from visual foundation models into 3D. We train a…
Generative Spatiotemporal Data Augmentation
Jinfan Zhou, Lixin Luo, Sungmin Eum +2
We explore spatiotemporal data augmentation using video foundation models to diversify both camera viewpoints and scene dynamics. Unlike existing approaches based on simple geometr…
Taming Feed-forward Reconstruction Models as Latent Encoders for 3D Generative Models
Suttisak Wizadwongsa, Jinfan Zhou, Edward Li +1
Recent AI-based 3D content creation has largely evolved along two paths: feed-forward image-to-3D reconstruction approaches and 3D generative models trained with 2D or 3D supervisi…
Shifted-Windows Transformers for the Detection of Cerebral Aneurysms in Microsurgery
Jinfan Zhou, William Muirhead, Simon C. Williams +3
Purpose: Microsurgical Aneurysm Clipping Surgery (MACS) carries a high risk for intraoperative aneurysm rupture. Automated recognition of instances when the aneurysm is exposed in…
Objective Surgical Skills Assessment and Tool Localization: Results from the MICCAI 2021 SimSurgSkill Challenge
Aneeq Zia, Kiran Bhattacharyya, Xi Liu +12
Timely and effective feedback within surgical training plays a critical role in developing the skills required to perform safe and efficient surgery. Feedback from expert surgeons,…