English
Related papers

Related papers: Endora: Video Generation Models as Endoscopy Simul…

200 papers

Accurate and robust tracking and reconstruction of the surgical scene is a critical enabling technology toward autonomous robotic surgery. Existing algorithms for 3D perception in surgery mainly rely on geometric information, while we…

Image and Video Processing · Electrical Eng. & Systems 2023-02-21 Shan Lin , Albert J. Miao , Jingpei Lu , Shunkai Yu , Zih-Yun Chiu , Florian Richter , Michael C. Yip

Long video generation remains a challenging and compelling topic in computer vision. Diffusion based models, among the various approaches to video generation, have achieved state of the art quality with their iterative denoising procedures.…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Siyang Zhang , Harry Yang , Ser-Nam Lim

Recent advances in foundational Video Diffusion Models (VDMs) have yielded significant progress. Yet, despite the remarkable visual quality of generated videos, reconstructing consistent 3D scenes from these outputs remains challenging, due…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Yisu Zhang , Chenjie Cao , Tengfei Wang , Xuhui Zuo , Junta Wu , Jianke Zhu , Chunchao Guo

Recent years have seen remarkable progress in autonomous driving, yet generalization to long-tail and open-world scenarios remains a major bottleneck for large-scale deployment. To address this challenge, some works use LLMs and VLMs for…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Hao Shao , Letian Wang , Yang Zhou , Yuxuan Hu , Zhuofan Zong , Steven L. Waslander , Wei Zhan , Hongsheng Li

The segmentation and tracking of living cells play a vital role within the biomedical domain, particularly in cancer research, drug development, and developmental biology. These are usually tedious and time-consuming tasks that are…

Image and Video Processing · Electrical Eng. & Systems 2024-03-27 Rüveyda Yilmaz , Dennis Eschweiler , Johannes Stegmaier

Video diffusion models are able to generate high-quality videos by learning strong spatial-temporal priors on large-scale datasets. In this paper, we aim to investigate whether such priors derived from a generative process are suitable for…

Computer Vision and Pattern Recognition · Computer Science 2024-11-13 Zejia Weng , Xitong Yang , Zhen Xing , Zuxuan Wu , Yu-Gang Jiang

Creating realistic human videos entails the challenge of being able to simultaneously generate both appearance, as well as motion. To tackle this challenge, we introduce G$^{3}$AN, a novel spatio-temporal generative model, which seeks to…

Computer Vision and Pattern Recognition · Computer Science 2020-06-16 Yaohui Wang , Piotr Bilinski , Francois Bremond , Antitza Dantcheva

Large-scale video generative models can synthesize diverse and realistic visual content for dynamic world creation, but they often lack element-wise controllability, hindering their use in editing scenes and training embodied AI agents. We…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Sicheng Mo , Ziyang Leng , Leon Liu , Weizhen Wang , Honglin He , Bolei Zhou

Research on video generation has recently made tremendous progress, enabling high-quality videos to be generated from text prompts or images. Adding control to the video generation process is an important goal moving forward and recent…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Zhengfei Kuang , Shengqu Cai , Hao He , Yinghao Xu , Hongsheng Li , Leonidas Guibas , Gordon Wetzstein

The healthcare industry has a growing need for realistic modeling and efficient simulation of surgical scenes. With effective models of deformable surgical scenes, clinicians are able to conduct surgical planning and surgery training on…

Image and Video Processing · Electrical Eng. & Systems 2024-04-25 Yuehao Wang , Bingchen Gong , Yonghao Long , Siu Hin Fan , Qi Dou

3D scene generation has long been dominated by 2D multi-view or video diffusion models. This is due not only to the lack of scene-level 3D latent representation, but also to the fact that most scene-level 3D visual data exists in the form…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Dongxu Wei , Qi Xu , Zhiqi Li , Hangning Zhou , Cong Qiu , Hailong Qin , Mu Yang , Zhaopeng Cui , Peidong Liu

We introduce Reangle-A-Video, a unified framework for generating synchronized multi-view videos from a single input video. Unlike mainstream approaches that train multi-view video diffusion models on large-scale 4D datasets, our method…

Computer Vision and Pattern Recognition · Computer Science 2025-09-11 Hyeonho Jeong , Suhyeon Lee , Jong Chul Ye

We present GEN3C, a generative video model with precise Camera Control and temporal 3D Consistency. Prior video models already generate realistic videos, but they tend to leverage little 3D information, leading to inconsistencies, such as…

Computer Vision and Pattern Recognition · Computer Science 2025-03-06 Xuanchi Ren , Tianchang Shen , Jiahui Huang , Huan Ling , Yifan Lu , Merlin Nimier-David , Thomas Müller , Alexander Keller , Sanja Fidler , Jun Gao

Recent advances in text-to-3D scene generation have demonstrated significant potential to transform content creation across multiple industries. Although the research community has made impressive progress in addressing the challenges of…

Generating videos predicting the future of a given sequence has been an area of active research in recent years. However, an essential problem remains unsolved: most of the methods require large computational cost and memory usage for…

Computer Vision and Pattern Recognition · Computer Science 2021-06-09 Naoya Fushishita , Antonio Tejero-de-Pablos , Yusuke Mukuta , Tatsuya Harada

Recent advancements in video generation have enabled the development of ``world models'' capable of simulating potential futures for robotics and planning. However, specifying precise goals for these models remains a challenge; text…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Nate Gillman , Yinghua Zhou , Zitian Tang , Evan Luo , Arjan Chakravarthy , Daksh Aggarwal , Michael Freeman , Charles Herrmann , Chen Sun

Recent advances in deep learning led to novel generative modeling techniques that achieve unprecedented quality in generated samples and performance in learning complex distributions in imaging data. These new models in medical image…

Computer Vision and Pattern Recognition · Computer Science 2018-06-15 Xiaoran Chen , Nick Pawlowski , Martin Rajchl , Ben Glocker , Ender Konukoglu

Recent advances in image editing, driven by image diffusion models, have shown remarkable progress. However, significant challenges remain, as these models often struggle to follow complex edit instructions accurately and frequently…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Noam Rotstein , Gal Yona , Daniel Silver , Roy Velich , David Bensaïd , Ron Kimmel

Video generative models have emerged as a promising robotics backbone, capable of generating videos that depict the completion of complex tasks across embodiments and environments. Recent work proposes robot foundation models that jointly…

Robotics · Computer Science 2026-05-28 Sizhe Lester Li , Evan Kim , Xingjian Bai , Tong Zhao , Tao Pang , Max Simchowitz , Vincent Sitzmann

Recent advances in generative video modeling, driven by large-scale datasets and powerful architectures, have yielded remarkable visual realism. However, emerging evidence suggests that simply scaling data and model size does not endow…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Ying Shen , Jerry Xiong , Tianjiao Yu , Ismini Lourentzou