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Reconstruction of deformable scenes from endoscopic videos is important for many applications such as intraoperative navigation, surgical visual perception, and robotic surgery. It is a foundational requirement for realizing autonomous…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Shreya Saha , Zekai Liang , Shan Lin , Jingpei Lu , Michael Yip , Sainan Liu

Endoscopy is essential in medical imaging, used for diagnosis, prognosis and treatment. Developing a robust dynamic 3D reconstruction pipeline for endoscopic videos could enhance visualization, improve diagnostic accuracy, aid in treatment…

Computer Vision and Pattern Recognition · Computer Science 2026-02-18 Laura Salort-Benejam , Antonio Agudo

Reconstruction of the soft tissues in robotic surgery from endoscopic stereo videos is important for many applications such as intra-operative navigation and image-guided robotic surgery automation. Previous works on this task mainly rely…

Computer Vision and Pattern Recognition · Computer Science 2022-07-01 Yuehao Wang , Yonghao Long , Siu Hin Fan , Qi Dou

Purpose: Surgical scene understanding plays a critical role in the technology stack of tomorrow's intervention-assisting systems in endoscopic surgeries. For this, tracking the endoscope pose is a key component, but remains challenging due…

Computer Vision and Pattern Recognition · Computer Science 2023-04-18 Michel Hayoz , Christopher Hahne , Mathias Gallardo , Daniel Candinas , Thomas Kurmann , Maximilian Allan , Raphael Sznitman

Reconstructing soft tissues from stereo endoscope videos is an essential prerequisite for many medical applications. Previous methods struggle to produce high-quality geometry and appearance due to their inadequate representations of 3D…

Computer Vision and Pattern Recognition · Computer Science 2023-09-06 Ruyi Zha , Xuelian Cheng , Hongdong Li , Mehrtash Harandi , Zongyuan Ge

Given that a conventional laparoscope only provides a two-dimensional (2-D) view, the detection and diagnosis of medical ailments can be challenging. To overcome the visual constraints associated with laparoscopy, the use of laparoscopic…

Computer Vision and Pattern Recognition · Computer Science 2023-10-19 Khoa Tuan Nguyen , Francesca Tozzi , Nikdokht Rashidian , Wouter Willaert , Joris Vankerschaver , Wesley De Neve

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

Reconstructing deformable surgical scenes from endoscopic videos is challenging and clinically important. Recent state-of-the-art methods based on implicit neural representations or 3D Gaussian splatting have made notable progress. However,…

Computer Vision and Pattern Recognition · Computer Science 2026-02-20 Jiwei Shan , Zeyu Cai , Cheng-Tai Hsieh , Yirui Li , Hao Liu , Lijun Han , Hesheng Wang , Shing Shin Cheng

Accurate 3D reconstruction from multi-view images is essential for downstream robotic tasks such as navigation, manipulation, and environment understanding. However, obtaining precise camera poses in real-world settings remains challenging,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-12 Sriram Srinivasan , Gautam Ramachandra

In the realm of robot-assisted minimally invasive surgery, dynamic scene reconstruction can significantly enhance downstream tasks and improve surgical outcomes. Neural Radiance Fields (NeRF)-based methods have recently risen to prominence…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Yiming Huang , Beilei Cui , Long Bai , Ziqi Guo , Mengya Xu , Mobarakol Islam , Hongliang Ren

Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) have emerged as powerful tools for 3D reconstruction and SLAM tasks. However, their performance depends heavily on accurate camera pose priors. Existing approaches attempt to…

Computer Vision and Pattern Recognition · Computer Science 2025-06-25 Qingsong Yan , Qiang Wang , Kaiyong Zhao , Jie Chen , Bo Li , Xiaowen Chu , Fei Deng

Robot-assisted minimally invasive surgery benefits from enhancing dynamic scene reconstruction, as it improves surgical outcomes. While Neural Radiance Fields (NeRF) have been effective in scene reconstruction, their slow inference speeds…

Computer Vision and Pattern Recognition · Computer Science 2024-09-11 Haoyu Zhao , Xingyue Zhao , Lingting Zhu , Weixi Zheng , Yongchao Xu

Recent advancements in 4D scene reconstruction using neural radiance fields (NeRF) have demonstrated the ability to represent dynamic scenes from multi-view videos. However, they fail to reconstruct the dynamic scenes and struggle to fit…

Computer Vision and Pattern Recognition · Computer Science 2024-08-14 Seoha Kim , Jeongmin Bae , Youngsik Yun , Hahyun Lee , Gun Bang , Youngjung Uh

Neural Radiance Fields (NeRF) is a cutting-edge neural network-based technique for novel view synthesis in 3D reconstruction. However, its significant computational demands pose challenges for deployment on mobile devices. While mesh-based…

Graphics · Computer Science 2025-04-07 Zhe Wang , Yifei Zhu

Recently, Neural Radiance Fields (NeRF) is revolutionizing the task of novel view synthesis (NVS) for its superior performance. In this paper, we propose to synthesize dynamic scenes. Extending the methods for static scenes to dynamic…

Computer Vision and Pattern Recognition · Computer Science 2022-10-12 Xiang Guo , Guanying Chen , Yuchao Dai , Xiaoqing Ye , Jiadai Sun , Xiao Tan , Errui Ding

Neural Radiance Fields, or NeRFs, have drastically improved novel view synthesis and 3D reconstruction for rendering. NeRFs achieve impressive results on object-centric reconstructions, but the quality of novel view synthesis with…

Computer Vision and Pattern Recognition · Computer Science 2023-09-06 Georgios Kopanas , George Drettakis

Neural radiance field (NeRF) attracts attention as a promising approach to reconstructing the 3D scene. As NeRF emerges, subsequent studies have been conducted to model dynamic scenes, which include motions or topological changes. However,…

Computer Vision and Pattern Recognition · Computer Science 2022-12-07 Hankyu Jang , Daeyoung Kim

Neural radiance fields (NeRF) bring a new wave for 3D interactive experiences. However, as an important part of the immersive experiences, the defocus effects have not been fully explored within NeRF. Some recent NeRF-based methods generate…

Computer Vision and Pattern Recognition · Computer Science 2022-08-11 Yinhuai Wang , Shuzhou Yang , Yujie Hu , Jian Zhang

We present the first method capable of photorealistically reconstructing deformable scenes using photos/videos captured casually from mobile phones. Our approach augments neural radiance fields (NeRF) by optimizing an additional continuous…

Computer Vision and Pattern Recognition · Computer Science 2021-09-13 Keunhong Park , Utkarsh Sinha , Jonathan T. Barron , Sofien Bouaziz , Dan B Goldman , Steven M. Seitz , Ricardo Martin-Brualla

Existing inverse rendering combined with neural rendering methods can only perform editable novel view synthesis on object-specific scenes, while we present intrinsic neural radiance fields, dubbed IntrinsicNeRF, which introduce intrinsic…

Computer Vision and Pattern Recognition · Computer Science 2023-08-30 Weicai Ye , Shuo Chen , Chong Bao , Hujun Bao , Marc Pollefeys , Zhaopeng Cui , Guofeng Zhang
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