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We tackle the challenge of generating dynamic 4D scenes from monocular, multi-object videos with heavy occlusions, and introduce GenMOJO, a novel approach that integrates rendering-based deformable 3D Gaussian optimization with generative…

Computer Vision and Pattern Recognition · Computer Science 2025-06-17 Wen-Hsuan Chu , Lei Ke , Jianmeng Liu , Mingxiao Huo , Pavel Tokmakov , Katerina Fragkiadaki

3D Gaussian Splatting has shown impressive novel view synthesis results; nonetheless, it is vulnerable to dynamic objects polluting the input data of an otherwise static scene, so called distractors. Distractors have severe impact on the…

Computer Vision and Pattern Recognition · Computer Science 2024-08-22 Paul Ungermann , Armin Ettenhofer , Matthias Nießner , Barbara Roessle

The creation of digital replicas of physical objects has valuable applications for the preservation and dissemination of tangible cultural heritage. However, existing methods are often slow, expensive, and require expert knowledge. We…

Computer Vision and Pattern Recognition · Computer Science 2024-10-01 Mahtab Dahaghin , Myrna Castillo , Kourosh Riahidehkordi , Matteo Toso , Alessio Del Bue

We propose a method to enhance 3D Gaussian Splatting (3DGS)~\cite{Kerbl2023}, addressing challenges in initialization, optimization, and density control. Gaussian Splatting is an alternative for rendering realistic images while supporting…

Computer Vision and Pattern Recognition · Computer Science 2025-07-02 Xingjun Wang , Lianlei Shan

3D Gaussian splatting (3DGS) offers the capability to achieve real-time high quality 3D scene rendering. However, 3DGS assumes that the scene is in a clear medium environment and struggles to generate satisfactory representations in…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Haoran Wang , Nantheera Anantrasirichai , Fan Zhang , David Bull

The advent of 3D Gaussian Splatting (3DGS) has recently brought about a revolution in the field of neural rendering, facilitating high-quality renderings at real-time speed. However, 3DGS heavily depends on the initialized point cloud…

Computer Vision and Pattern Recognition · Computer Science 2024-02-23 Kai Cheng , Xiaoxiao Long , Kaizhi Yang , Yao Yao , Wei Yin , Yuexin Ma , Wenping Wang , Xuejin Chen

Gaussian Splatting (GS) has proven to be highly effective in novel view synthesis, achieving high-quality and real-time rendering. However, its potential for reconstructing detailed 3D shapes has not been fully explored. Existing methods…

Graphics · Computer Science 2024-06-25 Baowen Zhang , Chuan Fang , Rakesh Shrestha , Yixun Liang , Xiaoxiao Long , Ping Tan

3D Gaussian Splatting (3DGS) provides an efficient method for high-quality scene reconstruction using anisotropic Gaussians. Recently, 3DGS-based methods have significantly improved the rendering quality of human avatars while enabling…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Hongzhe Liao , Chuhua Xian , Hongmin Cai , Haiyang Liu , Fa-Ting Hong

We introduce InsideOut, an extension of 3D Gaussian splatting (3DGS) that bridges the gap between high-fidelity RGB surface details and subsurface X-ray structures. The fusion of RGB and X-ray imaging is invaluable in fields such as medical…

Computer Vision and Pattern Recognition · Computer Science 2025-10-22 Jungmin Lee , Seonghyuk Hong , Juyong Lee , Jaeyoon Lee , Jongwon Choi

Recent advancements in 3D content generation from text or a single image struggle with limited high-quality 3D datasets and inconsistency from 2D multi-view generation. We introduce DiffSplat, a novel 3D generative framework that natively…

Computer Vision and Pattern Recognition · Computer Science 2025-01-29 Chenguo Lin , Panwang Pan , Bangbang Yang , Zeming Li , Yadong Mu

Reconstructing a 3D scene from images is challenging due to the different ways light interacts with surfaces depending on the viewer's position and the surface's material. In classical computer graphics, materials can be classified as…

Computer Vision and Pattern Recognition · Computer Science 2025-02-03 Mateusz Nowak , Wojciech Jarosz , Peter Chin

Transparent object manipulation remains a significant challenge in robotics due to the difficulty of acquiring accurate and dense depth measurements. Conventional depth sensors often fail with transparent objects, resulting in incomplete or…

Computer Vision and Pattern Recognition · Computer Science 2025-02-19 Jeongyun Kim , Jeongho Noh , Dong-Guw Lee , Ayoung Kim

As 3D Gaussian Splatting (3DGS) gains rapid adoption in safety-critical tasks for efficient novel-view synthesis from static images, how might an adversary tamper images to cause harm? We introduce ComplicitSplat, the first attack that…

Computer Vision and Pattern Recognition · Computer Science 2025-09-09 Matthew Hull , Haoyang Yang , Pratham Mehta , Mansi Phute , Aeree Cho , Haorang Wang , Matthew Lau , Wenke Lee , Wilian Lunardi , Martin Andreoni , Duen Horng Chau

Reconstructing urban scenes is challenging due to their complex geometries and the presence of potentially dynamic objects. 3D Gaussian Splatting (3DGS)-based methods have shown strong performance, but existing approaches often incorporate…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Ziwen Li , Jiaxin Huang , Runnan Chen , Yunlong Che , Yandong Guo , Tongliang Liu , Fakhri Karray , Mingming Gong

We propose WildSplatter, a feed-forward 3D Gaussian Splatting (3DGS) model for unconstrained images with unknown camera parameters and varying lighting conditions. 3DGS is an effective scene representation that enables high-quality,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Yuki Fujimura , Takahiro Kushida , Kazuya Kitano , Takuya Funatomi , Yasuhiro Mukaigawa

In this work, we propose a novel method to supervise 3D Gaussian Splatting (3DGS) scenes using optical tactile sensors. Optical tactile sensors have become widespread in their use in robotics for manipulation and object representation;…

Robotics · Computer Science 2024-08-19 Aiden Swann , Matthew Strong , Won Kyung Do , Gadiel Sznaier Camps , Mac Schwager , Monroe Kennedy

Primitive-based splatting methods like 3D Gaussian Splatting have revolutionized novel view synthesis with real-time rendering. However, their point-based representations remain incompatible with mesh-based pipelines that power AR/VR and…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Jan Held , Sanghyun Son , Renaud Vandeghen , Daniel Rebain , Matheus Gadelha , Yi Zhou , Anthony Cioppa , Ming C. Lin , Marc Van Droogenbroeck , Andrea Tagliasacchi

3D Gaussian Splatting (3DGS) has recently enabled real-time rendering of unbounded 3D scenes for novel view synthesis. However, this technique requires dense training views to accurately reconstruct 3D geometry. A limited number of input…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Haolin Xiong , Sairisheek Muttukuru , Rishi Upadhyay , Pradyumna Chari , Achuta Kadambi

Sparse-view 3D reconstruction is increasingly addressed with feed-forward splatting networks that predict explicit primitives directly from images. Yet most existing methods remain centered on Gaussian primitives and expose surfaces only…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Weijie Wang , Zimu Li , Jinchuan Shi , Zeyu Zhang , Botao Ye , Marc Pollefeys , Donny Y. Chen , Bohan Zhuang

This study addresses the challenge of generating online 3D Gaussian Splatting (3DGS) models from RGB-only frames. Previous studies have employed dense SLAM techniques to estimate 3D scenes from keyframes for 3DGS model construction.…

Computer Vision and Pattern Recognition · Computer Science 2025-09-08 Byeonggwon Lee , Junkyu Park , Khang Truong Giang , Soohwan Song