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Capturing and labeling real-world 3D data is laborious and time-consuming, which makes it costly to train strong 3D models. To address this issue, recent works present a simple method by generating randomized 3D scenes without simulation…

Computer Vision and Pattern Recognition · Computer Science 2023-08-08 Lanxiao Li , Michael Heizmann

Recent advancements in dynamic 3D scene reconstruction have shown promising results, enabling high-fidelity 3D novel view synthesis with improved temporal consistency. Among these, 4D Gaussian Splatting (4DGS) has emerged as an appealing…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Seungjun Oh , Younggeun Lee , Hyejin Jeon , Eunbyung Park

Novel view synthesis from a single image has recently attracted a lot of attention, and it has been primarily advanced by 3D deep learning and rendering techniques. However, most work is still limited by synthesizing new views within…

Computer Vision and Pattern Recognition · Computer Science 2022-03-18 Xuanchi Ren , Xiaolong Wang

The paper surveys variational approaches for image reconstruction in dynamic inverse problems. Emphasis is on methods that rely on parametrised temporal models. These are here encoded as diffeomorphic deformations with time dependent…

Image and Video Processing · Electrical Eng. & Systems 2020-07-21 Andreas Hauptmann , Ozan Öktem , Carola Schönlieb

We present a novel approach for real-time joint reconstruction of 3D scene motion and geometry from binocular stereo videos. Our approach is based on a novel variational halfway-domain scene flow formulation, which allows us to obtain…

Computer Vision and Pattern Recognition · Computer Science 2016-10-25 Lucas Thies , Michael Zollhöfer , Christian Richardt , Christian Theobalt , Günther Greiner

Novel view synthesis of dynamic scenes is becoming important in various applications, including augmented and virtual reality. We propose a novel 4D Gaussian Splatting (4DGS) algorithm for dynamic scenes from casually recorded monocular…

Computer Vision and Pattern Recognition · Computer Science 2024-11-14 Mijeong Kim , Jongwoo Lim , Bohyung Han

High dynamic range (HDR) video reconstruction from sequences captured with alternating exposures is a very challenging problem. Existing methods often align low dynamic range (LDR) input sequence in the image space using optical flow, and…

Computer Vision and Pattern Recognition · Computer Science 2021-08-24 Guanying Chen , Chaofeng Chen , Shi Guo , Zhetong Liang , Kwan-Yee K. Wong , Lei Zhang

The challenge of dynamic view synthesis from dynamic monocular videos, i.e., synthesizing novel views for free viewpoints given a monocular video of a dynamic scene captured by a moving camera, mainly lies in accurately modeling the…

Computer Vision and Pattern Recognition · Computer Science 2024-08-22 Meng You , Junhui Hou

Existing monocular depth estimation methods have achieved excellent robustness in diverse scenes, but they can only retrieve affine-invariant depth, up to an unknown scale and shift. However, in some video-based scenarios such as video…

Computer Vision and Pattern Recognition · Computer Science 2023-04-07 Guangkai Xu , Wei Yin , Hao Chen , Chunhua Shen , Kai Cheng , Feng Wu , Feng Zhao

Novel view synthesis from monocular videos of dynamic scenes with unknown camera poses remains a fundamental challenge in computer vision and graphics. While recent advances in 3D representations such as Neural Radiance Fields (NeRF) and 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-11-10 Mengqi Guo , Bo Xu , Yanyan Li , Gim Hee Lee

We present an algorithm for reconstructing the radiance field of a large-scale scene from a single casually captured video. The task poses two core challenges. First, most existing radiance field reconstruction approaches rely on accurate…

Computer Vision and Pattern Recognition · Computer Science 2023-03-27 Andreas Meuleman , Yu-Lun Liu , Chen Gao , Jia-Bin Huang , Changil Kim , Min H. Kim , Johannes Kopf

Although dynamic scene reconstruction has long been a fundamental challenge in 3D vision, the recent emergence of 3D Gaussian Splatting (3DGS) offers a promising direction by enabling high-quality, real-time rendering through explicit…

Graphics · Computer Science 2025-05-29 Zehao Li , Hao Jiang , Yujun Cai , Jianing Chen , Baolong Bi , Shuqin Gao , Honglong Zhao , Yiwei Wang , Tianlu Mao , Zhaoqi Wang

We address the problem of dynamic scene reconstruction from sparse-view videos. Prior work often requires dense multi-view captures with hundreds of calibrated cameras (e.g. Panoptic Studio). Such multi-view setups are prohibitively…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Zihan Wang , Jeff Tan , Tarasha Khurana , Neehar Peri , Deva Ramanan

Generative reconstruction methods compute the 3D configuration (such as pose and/or geometry) of a shape by optimizing the overlap of the projected 3D shape model with images. Proper handling of occlusions is a big challenge, since the…

Computer Vision and Pattern Recognition · Computer Science 2016-02-12 Helge Rhodin , Nadia Robertini , Christian Richardt , Hans-Peter Seidel , Christian Theobalt

Recent 3D feed-forward models, such as the Visual Geometry Grounded Transformer (VGGT), have shown strong capability in inferring 3D attributes of static scenes. However, since they are typically trained on static datasets, these models…

Computer Vision and Pattern Recognition · Computer Science 2026-05-15 Kaichen Zhou , Yuhan Wang , Grace Chen , Xinhai Chang , Gaspard Beaudouin , Fangneng Zhan , Paul Pu Liang , Mengyu Wang

Humans can naturally identify and mentally complete occluded objects in cluttered environments. However, imparting similar cognitive ability to robotics remains challenging even with advanced reconstruction techniques, which models scenes…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Zesong Yang , Bangbang Yang , Wenqi Dong , Chenxuan Cao , Liyuan Cui , Yuewen Ma , Zhaopeng Cui , Hujun Bao

Operating effectively in novel real-world environments requires robotic systems to estimate and interact with previously unseen objects. Current state-of-the-art models address this challenge by using large amounts of training data and…

Robotics · Computer Science 2026-02-06 Octavio Arriaga , Proneet Sharma , Jichen Guo , Marc Otto , Siddhant Kadwe , Rebecca Adam

Recent developments in 3D Gaussian Splatting have made significant advances in surface reconstruction. However, scaling these methods to large-scale scenes remains challenging due to high computational demands and the complex dynamic…

Graphics · Computer Science 2025-06-24 Shihan Chen , Zhaojin Li , Zeyu Chen , Qingsong Yan , Gaoyang Shen , Ran Duan

Cinematic video production requires control over scene-subject composition and camera movement, but live-action shooting remains costly due to the need for constructing physical sets. To address this, we introduce the task of cinematic…

Computer Vision and Pattern Recognition · Computer Science 2026-02-09 Kaiyi Huang , Yukun Huang , Yu Li , Jianhong Bai , Xintao Wang , Zinan Lin , Xuefei Ning , Jiwen Yu , Pengfei Wan , Yu Wang , Xihui Liu

Given a monocular video, the goal of video re-rendering is to generate views of the scene from a novel camera trajectory. Existing methods face two distinct challenges. Geometrically unconditioned models lack spatial awareness, leading to…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Mingyang Xie , Numair Khan , Tianfu Wang , Naina Dhingra , Seonghyeon Nam , Haitao Yang , Zhuo Hui , Christopher Metzler , Andrea Vedaldi , Hamed Pirsiavash , Lei Luo
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