English
Related papers

Related papers: TraceFlow: Dynamic 3D Reconstruction of Specular S…

200 papers

In this paper, we aim to model 3D scene geometry, appearance, and physical information just from dynamic multi-view videos in the absence of any human labels. By leveraging physics-informed losses as soft constraints or integrating simple…

Computer Vision and Pattern Recognition · Computer Science 2025-08-14 Jinxi Li , Ziyang Song , Bo Yang

Gaussian Splatting have demonstrated remarkable novel view synthesis performance at high rendering frame rates. Optimization-based inverse rendering within complex capture scenarios remains however a challenging problem. A particular case…

Graphics · Computer Science 2025-12-08 Mae Younes , Adnane Boukhayma

We present Neural Reflectance Fields, a novel deep scene representation that encodes volume density, normal and reflectance properties at any 3D point in a scene using a fully-connected neural network. We combine this representation with a…

Computer Vision and Pattern Recognition · Computer Science 2020-08-18 Sai Bi , Zexiang Xu , Pratul Srinivasan , Ben Mildenhall , Kalyan Sunkavalli , Miloš Hašan , Yannick Hold-Geoffroy , David Kriegman , Ravi Ramamoorthi

Novel view synthesis has been greatly enhanced by the development of radiance field methods. The introduction of 3D Gaussian Splatting (3DGS) has effectively addressed key challenges, such as long training times and slow rendering speeds,…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Gopi Raju Matta , Reddypalli Trisha , Kaushik Mitra

3D Gaussian Splatting (3DGS) demonstrates unparalleled superior performance in 3D scene reconstruction. However, 3DGS heavily relies on the sharp images. Fulfilling this requirement can be challenging in real-world scenarios especially when…

Computer Vision and Pattern Recognition · Computer Science 2024-12-25 Yijia Guo , Liwen Hu , Yuanxi Bai , Jiawei Yao , Lei Ma , Tiejun Huang

Dynamic urban scene modeling is a rapidly evolving area with broad applications. While current approaches leveraging neural radiance fields or Gaussian Splatting have achieved fine-grained reconstruction and high-fidelity novel view…

Computer Vision and Pattern Recognition · Computer Science 2026-05-11 Yuru Xiao , Zihan Lin , Chao Lu , Deming Zhai , Kui Jiang , Wenbo Zhao , Wei Zhang , Junjun Jiang , Huanran Wang , Xianming Liu

Transient objects in video sequences can significantly degrade the quality of 3D scene reconstructions. To address this challenge, we propose T-3DGS, a novel framework that robustly filters out transient distractors during 3D reconstruction…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Alexander Markin , Vadim Pryadilshchikov , Artem Komarichev , Ruslan Rakhimov , Peter Wonka , Evgeny Burnaev

Recent advances in view synthesis and real-time rendering have achieved photorealistic quality at impressive rendering speeds. While Radiance Field-based methods achieve state-of-the-art quality in challenging scenarios such as in-the-wild…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Michael Niemeyer , Fabian Manhardt , Marie-Julie Rakotosaona , Michael Oechsle , Daniel Duckworth , Rama Gosula , Keisuke Tateno , John Bates , Dominik Kaeser , Federico Tombari

3D Gaussian Splatting (3DGS) has emerged as a prominent 3D representation for high-fidelity and real-time rendering. Prior work has coupled physics simulation with Gaussians, but predominantly targets soft, deformable materials, leaving…

Computer Vision and Pattern Recognition · Computer Science 2026-01-15 Bei Huang , Yixin Chen , Ruijie Lu , Gang Zeng , Hongbin Zha , Yuru Pei , Siyuan Huang

Polarization-aware Neural Radiance Fields (NeRF) enable novel view synthesis of specular-reflection scenes but face challenges in slow training, inefficient rendering, and strong dependencies on material/viewpoint assumptions. However, 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Derui Shan , Qian Qiao , Hao Lu , Tao Du , Peng Lu

3D Gaussian Splatting (3DGS) has gained significant attention for its real-time, photo-realistic rendering in novel-view synthesis and 3D modeling. However, existing methods struggle with accurately modeling scenes affected by transient…

Computer Vision and Pattern Recognition · Computer Science 2025-07-30 Chuanyu Fu , Yuqi Zhang , Kunbin Yao , Guanying Chen , Yuan Xiong , Chuan Huang , Shuguang Cui , Xiaochun Cao

Scene flow is the dense 3D reconstruction of motion and geometry of a scene. Most state-of-the-art methods use a pair of stereo images as input for full scene reconstruction. These methods depend a lot on the quality of the RGB images and…

Computer Vision and Pattern Recognition · Computer Science 2020-08-20 Rishav , Ramy Battrawy , René Schuster , Oliver Wasenmüller , Didier Stricker

Recent advancements in 3D Gaussian Splatting(3DGS) have significantly improved semantic scene understanding, enabling natural language queries to localize objects within a scene. However, existing methods primarily focus on embedding…

Computer Vision and Pattern Recognition · Computer Science 2025-03-07 Xihan Wang , Dianyi Yang , Yu Gao , Yufeng Yue , Yi Yang , Mengyin Fu

Scene reconstruction has emerged as a central challenge in computer vision, with approaches such as Neural Radiance Fields (NeRF) and Gaussian Splatting achieving remarkable progress. While Gaussian Splatting demonstrates strong performance…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Alexander Valverde , Brian Xu , Yuyin Zhou , Meng Xu , Hongyun Wang

Representing and rendering dynamic scenes has been an important but challenging task. Especially, to accurately model complex motions, high efficiency is usually hard to guarantee. To achieve real-time dynamic scene rendering while also…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Guanjun Wu , Taoran Yi , Jiemin Fang , Lingxi Xie , Xiaopeng Zhang , Wei Wei , Wenyu Liu , Qi Tian , Xinggang Wang

Dynamic scene representation and reconstruction have undergone transformative advances in recent years, catalyzed by breakthroughs in neural radiance fields and 3D Gaussian splatting techniques. While initially developed for static…

Computer Vision and Pattern Recognition · Computer Science 2025-05-23 Jinlong Fan , Xuepu Zeng , Jing Zhang , Mingming Gong , Yuxiang Yang , Dacheng Tao

Simultaneously localizing camera poses and constructing Gaussian radiance fields in dynamic scenes establish a crucial bridge between 2D images and the 4D real world. Instead of removing dynamic objects as distractors and reconstructing…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Yanyan Li , Youxu Fang , Zunjie Zhu , Kunyi Li , Yong Ding , Federico Tombari

Recent advances in novel view synthesis (NVS) have enabled real-time rendering with 3D Gaussian Splatting (3DGS). However, existing methods struggle with artifacts and missing regions when rendering from viewpoints that deviate from the…

Computer Vision and Pattern Recognition · Computer Science 2025-08-11 Minsu Kim , Subin Jeon , In Cho , Mijin Yoo , Seon Joo Kim

Dynamic scene reconstruction is a long-term challenge in 3D vision. Recent methods extend 3D Gaussian Splatting to dynamic scenes via additional deformation fields and apply explicit constraints like motion flow to guide the deformation.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 DaDong Jiang , Zhihui Ke , Xiaobo Zhou , Zhi Hou , Xianghui Yang , Wenbo Hu , Tie Qiu , Chunchao Guo

We present Seen2Scene, the first flow matching-based approach that trains directly on incomplete, real-world 3D scans for scene completion and generation. Unlike prior methods that rely on complete and hence synthetic 3D data, our approach…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Quan Meng , Yujin Chen , Lei Li , Matthias Nießner , Angela Dai