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Recovering 3D information from scenes via multi-view stereo reconstruction (MVS) and novel view synthesis (NVS) is inherently challenging, particularly in scenarios involving sparse-view setups. The advent of 3D Gaussian Splatting (3DGS)…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Shubhendu Jena , Shishir Reddy Vutukur , Adnane Boukhayma

Gaze estimation encounters generalization challenges when dealing with out-of-distribution data. To address this problem, recent methods use neural radiance fields (NeRF) to generate augmented data. However, existing methods based on NeRF…

Computer Vision and Pattern Recognition · Computer Science 2025-07-10 Xiaobao Wei , Peng Chen , Guangyu Li , Ming Lu , Hui Chen , Feng Tian

In this paper, we present a novel differentiable point-based rendering framework to achieve photo-realistic relighting. To make the reconstructed scene relightable, we enhance vanilla 3D Gaussians by associating extra properties, including…

Computer Vision and Pattern Recognition · Computer Science 2024-08-09 Jian Gao , Chun Gu , Youtian Lin , Zhihao Li , Hao Zhu , Xun Cao , Li Zhang , Yao Yao

3D scene stylization extends the work of neural style transfer to 3D. A vital challenge in this problem is to maintain the uniformity of the stylized appearance across multiple views. A vast majority of the previous works achieve this by…

Computer Vision and Pattern Recognition · Computer Science 2024-09-09 Abhishek Saroha , Mariia Gladkova , Cecilia Curreli , Dominik Muhle , Tarun Yenamandra , Daniel Cremers

Neural rendering has demonstrated remarkable success in high-quality 3D neural reconstruction and novel view synthesis with dense input views and accurate poses. However, applying it to extremely sparse, unposed views in unbounded 360{\deg}…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Chong Bao , Xiyu Zhang , Zehao Yu , Jiale Shi , Guofeng Zhang , Songyou Peng , Zhaopeng Cui

3D Gaussian Splatting (3DGS) leverages densely distributed Gaussian primitives for high-quality scene representation and reconstruction. While existing 3DGS methods perform well in scenes with minor view variation, large view changes from…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Chenhao Zhang , Yuanping Cao , Lei Zhang

We propose 3D Super Resolution (3DSR), a novel 3D Gaussian-splatting-based super-resolution framework that leverages off-the-shelf diffusion-based 2D super-resolution models. 3DSR encourages 3D consistency across views via the use of an…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Yi-Ting Chen , Ting-Hsuan Liao , Pengsheng Guo , Alexander Schwing , Jia-Bin Huang

Inverse rendering seeks to reconstruct both geometry and spatially varying BRDFs (SVBRDFs) from captured images. To address the inherent ill-posedness of inverse rendering, basis BRDF representations are commonly used, modeling SVBRDFs as…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Hoon-Gyu Chung , Seokjun Choi , Seung-Hwan Baek

The boundary representation (B-Rep) models a 3D solid as its explicit boundaries: trimmed corners, edges, and faces. Recovering B-Rep representation from unstructured data is a challenging and valuable task of computer vision and graphics.…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Jiaxing Yu , Dongyang Ren , Hangyu Xu , Zhouyuxiao Yang , Yuanqi Li , Jie Guo , Zhengkang Zhou , Yanwen Guo

3D Gaussian Splatting has achieved impressive performance in novel view synthesis with real-time rendering capabilities. However, reconstructing high-quality surfaces with fine details using 3D Gaussians remains a challenging task. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Jiepeng Wang , Yuan Liu , Peng Wang , Cheng Lin , Junhui Hou , Xin Li , Taku Komura , Wenping Wang

We propose an analysis-by-synthesis method for fast multi-view 3D reconstruction of opaque objects with arbitrary materials and illumination. State-of-the-art methods use both neural surface representations and neural rendering. While…

Computer Vision and Pattern Recognition · Computer Science 2022-12-09 Markus Worchel , Rodrigo Diaz , Weiwen Hu , Oliver Schreer , Ingo Feldmann , Peter Eisert

Research on differentiable scene representations is consistently moving towards more efficient, real-time models. Recently, this has led to the popularization of splatting methods, which eschew the traditional ray-based rendering of…

Computer Vision and Pattern Recognition · Computer Science 2025-02-04 Shrisudhan Govindarajan , Daniel Rebain , Kwang Moo Yi , Andrea Tagliasacchi

Real objects that inhabit the physical world follow physical laws and thus behave plausibly during interaction with other physical objects. However, current methods that perform 3D reconstructions of real-world scenes from multi-view 2D…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Yuqiu Liu , Jialin Song , Marissa Ramirez de Chanlatte , Rochishnu Chowdhury , Rushil Paresh Desai , Wuyang Chen , Daniel Martin , Michael W. Mahoney

Underwater 3D scene reconstruction faces severe challenges from light absorption, scattering, and turbidity, which degrade geometry and color fidelity in traditional methods like Neural Radiance Fields (NeRF). While NeRF extensions such as…

Computer Vision and Pattern Recognition · Computer Science 2025-08-11 Wenpeng Xing , Jie Chen , Zaifeng Yang , Changting Lin , Jianfeng Dong , Chaochao Chen , Xun Zhou , Meng Han

3D Gaussian Splatting (3DGS) has transformed novel-view synthesis with its fast, interpretable, and high-fidelity rendering. However, its resource requirements limit its usability. Especially on constrained devices, training performance…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Saswat Subhajyoti Mallick , Rahul Goel , Bernhard Kerbl , Francisco Vicente Carrasco , Markus Steinberger , Fernando De La Torre

Reconstructing objects and extracting high-quality surfaces play a vital role in the real world. Current 4D representations show the ability to render high-quality novel views for dynamic objects, but cannot reconstruct high-quality meshes…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Shuai Zhang , Guanjun Wu , Zhoufeng Xie , Xinggang Wang , Bin Feng , Wenyu Liu

We propose PixelGaussian, an efficient feed-forward framework for learning generalizable 3D Gaussian reconstruction from arbitrary views. Most existing methods rely on uniform pixel-wise Gaussian representations, which learn a fixed number…

Computer Vision and Pattern Recognition · Computer Science 2024-10-25 Xin Fei , Wenzhao Zheng , Yueqi Duan , Wei Zhan , Masayoshi Tomizuka , Kurt Keutzer , Jiwen Lu

Photographs captured in unstructured tourist environments frequently exhibit variable appearances and transient occlusions, challenging accurate scene reconstruction and inducing artifacts in novel view synthesis. Although prior approaches…

Computer Vision and Pattern Recognition · Computer Science 2024-06-18 Jiacong Xu , Yiqun Mei , Vishal M. Patel

3D Gaussian Splatting (GS) enables highly photorealistic scene reconstruction from posed image sequences but struggles with viewpoint extrapolation due to its anisotropic nature, leading to overfitting and poor generalization, particularly…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Shuohan Tao , Boyao Zhou , Hanzhang Tu , Yuwang Wang , Yebin Liu

Understanding dynamic scenes from casual videos is critical for scalable robot learning, yet four-dimensional (4D) reconstruction under strictly monocular settings remains highly ill-posed. To address this challenge, our key insight is that…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Can Li , Jie Gu , Jingmin Chen , Fangzhou Qiu , Lei Sun
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