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Related papers: Flash-Splat: 3D Reflection Removal with Flash Cues…

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3D Gaussian Splats (3DGS) have proven a versatile rendering primitive, both for inverse rendering as well as real-time exploration of scenes. In these applications, coherence across camera frames and multiple views is crucial, be it for…

We propose Transmission-Reflection Gaussians (TR-Gaussians), a novel 3D-Gaussian-based representation for high-fidelity rendering of planar transmission and reflection, which are ubiquitous in indoor scenes. Our method combines 3D Gaussians…

Graphics · Computer Science 2025-11-18 Yong Liu , Keyang Ye , Tianjia Shao , Kun Zhou

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

The recent introduction of 3D Gaussian Splatting (3DGS) has significantly advanced novel view synthesis. Several studies have further improved the rendering quality of 3DGS, yet they still exhibit noticeable visual discrepancies when…

Computer Vision and Pattern Recognition · Computer Science 2025-11-20 Junseo Koo , Jinseo Jeong , Gunhee Kim

3D modeling of highly reflective objects remains challenging due to strong view-dependent appearances. While previous SDF-based methods can recover high-quality meshes, they are often time-consuming and tend to produce over-smoothed…

Computer Vision and Pattern Recognition · Computer Science 2025-06-17 Jinguang Tong , Xuesong li , Fahira Afzal Maken , Sundaram Muthu , Lars Petersson , Chuong Nguyen , Hongdong Li

In this paper, we aim ambitiously for a realistic yet challenging problem, namely, how to reconstruct high-quality 3D scenes from sparse low-resolution views that simultaneously suffer from deficient perspectives and clarity. Whereas…

Computer Vision and Pattern Recognition · Computer Science 2025-03-07 Yecong Wan , Mingwen Shao , Yuanshuo Cheng , Wangmeng Zuo

3D Gaussian Splatting has recently emerged as a powerful representation that can synthesize remarkable novel views using consistent multi-view images as input. However, we notice that images captured in dark environments where the scenes…

Computer Vision and Pattern Recognition · Computer Science 2024-08-21 Sheng Ye , Zhen-Hui Dong , Yubin Hu , Yu-Hui Wen , Yong-Jin Liu

Novel-view synthesis and 3D reconstruction from sparse posed images are central to robotics and AR/VR. Yet, feed-forward 3D Gaussian reconstruction fails under lowlight due to noise, color shifts, and unreliable correspondence. We propose…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Fuzhen Jiang , Zengtian Xie , Zhuoran Li

While existing feed-forward Gaussian splatting models offer computational efficiency and can generalize to sparse view settings, their performance is fundamentally constrained by relying on a single forward pass for inference. We propose…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Haofei Xu , Daniel Barath , Andreas Geiger , Marc Pollefeys

3D Gaussian Splatting (3DGS) has significantly advanced 3D scene reconstruction and novel view synthesis. However, like Neural Radiance Fields (NeRF), 3DGS struggles with accurately modeling physical reflections, particularly in mirrors,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-12 Jiarui Meng , Haijie Li , Yanmin Wu , Qiankun Gao , Shuzhou Yang , Jian Zhang , Siwei Ma

Recent advancements in 3D Gaussian Splatting (3DGS) and Neural Radiance Fields (NeRF) have achieved impressive results in real-time 3D reconstruction and novel view synthesis. However, these methods struggle in large-scale, unconstrained…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Niluthpol Chowdhury Mithun , Tuan Pham , Qiao Wang , Ben Southall , Kshitij Minhas , Bogdan Matei , Stephan Mandt , Supun Samarasekera , Rakesh Kumar

We present FlashSLAM, a novel SLAM approach that leverages 3D Gaussian Splatting for efficient and robust 3D scene reconstruction. Existing 3DGS-based SLAM methods often fall short in sparse view settings and during large camera movements…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Phu Pham , Damon Conover , Aniket Bera

We present a spatial and angular Gaussian based representation and a triple splatting process, for real-time, high-quality novel lighting-and-view synthesis from multi-view point-lit input images. To describe complex appearance, we employ a…

Computer Vision and Pattern Recognition · Computer Science 2024-10-16 Zoubin Bi , Yixin Zeng , Chong Zeng , Fan Pei , Xiang Feng , Kun Zhou , Hongzhi Wu

We introduce pixelSplat, a feed-forward model that learns to reconstruct 3D radiance fields parameterized by 3D Gaussian primitives from pairs of images. Our model features real-time and memory-efficient rendering for scalable training as…

Computer Vision and Pattern Recognition · Computer Science 2024-04-08 David Charatan , Sizhe Li , Andrea Tagliasacchi , Vincent Sitzmann

Photorealistic 3D reconstruction of unstructured real-world scenes remains challenging due to complex illumination variations and transient occlusions. Existing methods based on Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS)…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Yuzhou Tang , Dejun Xu , Yongjie Hou , Zhenzhong Wang , Min Jiang

We introduce a method for using event camera data in novel view synthesis via Gaussian Splatting. Event cameras offer exceptional temporal resolution and a high dynamic range. Leveraging these capabilities allows us to effectively address…

Computer Vision and Pattern Recognition · Computer Science 2025-05-22 Toshiya Yura , Ashkan Mirzaei , Igor Gilitschenski

Gaussian Splatting (GS) has become one of the most important neural rendering algorithms. GS represents 3D scenes using Gaussian components with trainable color and opacity. This representation achieves high-quality renderings with fast…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Krzysztof Byrski , Grzegorz Wilczyński , Weronika Smolak-Dyżewska , Piotr Borycki , Dawid Baran , Sławomir Tadeja , Przemysław Spurek

We propose a 3D Gaussian splatting-based framework for outdoor relighting that leverages intrinsic image decomposition to precisely integrate sunlight, sky radiance, and indirect lighting from unconstrained photo collections. Unlike prior…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Haiyang Bai , Jiaqi Zhu , Songru Jiang , Wei Huang , Tao Lu , Yuanqi Li , Jie Guo , Runze Fu , Yanwen Guo , Lijun Chen

In inverse rendering, accurately modeling visibility and indirect radiance for incident light is essential for capturing secondary effects. Due to the absence of a powerful Gaussian ray tracer, previous 3DGS-based methods have either…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Chun Gu , Xiaofei Wei , Zixuan Zeng , Yuxuan Yao , Li Zhang

We present TranSplat, a method for instant, accurate object relighting within the Gaussian Splatting (GS) framework. Rather than relying on costly inverse rendering routines, we propose a BRDF-free radiance transfer strategy that…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Boyang Tony Yu , Yanlin Jin , Yun He , Akshat Dave , Ravi Ramamoorthi , Guha Balakrishnan