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20232025
most citedEndora: Video Generation Models as Endoscopy Simulators

1 citations · 1 across the 6 of their papers we have counts for

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cs.CV2025

First Frame Is the Place to Go for Video Content Customization

Jingxi Chen, Zongxia Li, Zhichao Liu +6

What role does the first frame play in video generation models? Traditionally, it's viewed as the spatial-temporal starting point of a video, merely a seed for subsequent animation…

cs.CV2025

Generalized Dynamics Generation towards Scannable Physical World Model

Yichen Li, Zhiyi Li, Brandon Feng +2

Digital twin worlds with realistic interactive dynamics presents a new opportunity to develop generalist embodied agents in scannable environments with complex physical behaviors.…

cs.CV2025

IR3D-Bench: Evaluating Vision-Language Model Scene Understanding as Agentic Inverse Rendering

Parker Liu, Chenxin Li, Zhengxin Li +7

Vision-language models (VLMs) excel at descriptive tasks, but whether they truly understand scenes from visual observations remains uncertain. We introduce IR3D-Bench, a benchmark…

cs.CV2024

EndoSparse: Real-Time Sparse View Synthesis of Endoscopic Scenes using Gaussian Splatting

Chenxin Li, Brandon Y. Feng, Yifan Liu +4

3D reconstruction of biological tissues from a collection of endoscopic images is a key to unlock various important downstream surgical applications with 3D capabilities. Existing…

cs.CV20241 cited

Endora: Video Generation Models as Endoscopy Simulators

Chenxin Li, Hengyu Liu, Yifan Liu +6

Generative models hold promise for revolutionizing medical education, robot-assisted surgery, and data augmentation for machine learning. Despite progress in generating 2D medical…

cs.CV2023

Shielding the Unseen: Privacy Protection through Poisoning NeRF with Spatial Deformation

Yihan Wu, Brandon Y. Feng, Heng Huang

In this paper, we introduce an innovative method of safeguarding user privacy against the generative capabilities of Neural Radiance Fields (NeRF) models. Our novel poisoning attac…