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Recently, the 3D Gaussian Splatting (3D-GS) method has achieved great success in novel view synthesis, providing real-time rendering while ensuring high-quality rendering results. However, this method faces challenges in modeling specular…

Computer Vision and Pattern Recognition · Computer Science 2024-09-11 Zhiru Wang , Shiyun Xie , Chengwei Pan , Guoping Wang

Synthesizing novel views of large-scale scenes from unconstrained in-the-wild images is an important but challenging task in computer vision. Existing methods, which optimize per-image appearance and transient occlusion through implicit…

Computer Vision and Pattern Recognition · Computer Science 2026-02-02 Yiqing Li , Xuan Wang , Jiawei Wu , Yikun Ma , Zhi Jin

Recent advancements in 3D Gaussian Splatting (3D-GS) have demonstrated the potential of using 3D Gaussian primitives for high-speed, high-fidelity, and cost-efficient novel view synthesis from continuously calibrated input views. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-16 Jingqian Wu , Shuo Zhu , Chutian Wang , Boxin Shi , Edmund Y. Lam

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

This paper addresses the problem of dynamic scene surface reconstruction using Gaussian Splatting (GS), aiming to recover temporally consistent geometry. While existing GS-based dynamic surface reconstruction methods can yield superior…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Renjie Wu , Hongdong Li , Jose M. Alvarez , Miaomiao Liu

High-dynamic scene reconstruction aims to represent static background with rigid spatial features and dynamic objects with deformed continuous spatiotemporal features. Typically, existing methods adopt unified representation model (e.g.,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Hanyu Zhou , Haonan Wang , Haoyue Liu , Yuxing Duan , Luxin Yan , Gim Hee Lee

Given just a few glimpses of a scene, can you imagine the movie playing out as the camera glides through it? That's the lens we take on \emph{sparse-input novel view synthesis}, not only as filling spatial gaps between widely spaced views,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Yan Xu , Yixing Wang , Stella X. Yu

While 3D Gaussian Splatting (3DGS) has revolutionized real-time photorealistic view synthesis, its fundamental reliance on symmetric Gaussian distributions introduces visual artifacts that hinder accurate spatial data exploration.…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Beizhen Zhao , Yifan Zhou , Gaochao Song , Ziran Yin , Hao Wang

3D Gaussian Splatting represents a breakthrough in the field of novel view synthesis. It establishes Gaussians as core rendering primitives for highly accurate real-world environment reconstruction. Recent advances have drastically…

Graphics · Computer Science 2025-06-25 Jonathan Haberl , Philipp Fleck , Clemens Arth

Dynamic novel view synthesis (NVS) is essential for creating immersive experiences. Existing approaches have advanced dynamic NVS by introducing 3D Gaussian Splatting (3DGS) with implicit deformation fields or indiscriminately assigned…

Computer Vision and Pattern Recognition · Computer Science 2025-12-17 Kaizhe Zhang , Yijie Zhou , Weizhan Zhang , Caixia Yan , Haipeng Du , yugui xie , Yu-Hui Wen , Yong-Jin Liu

Generalizable Gaussian Splatting aims to synthesize novel views for unseen scenes without per-scene optimization. In particular, recent advancements utilize feed-forward networks to predict per-pixel Gaussian parameters, enabling…

Computer Vision and Pattern Recognition · Computer Science 2025-08-29 Yuxi Hu , Jun Zhang , Kuangyi Chen , Zhe Zhang , Friedrich Fraundorfer

Over the past year, 3D Gaussian Splatting (3DGS) has received significant attention for its ability to represent 3D scenes in a perceptually accurate manner. However, it can require a substantial amount of storage since each splat's…

Computer Vision and Pattern Recognition · Computer Science 2025-04-11 Brent Zoomers , Maarten Wijnants , Ivan Molenaers , Joni Vanherck , Jeroen Put , Lode Jorissen , Nick Michiels

State-of-the-art novel view synthesis methods achieve impressive results for multi-view captures of static 3D scenes. However, the reconstructed scenes still lack "liveliness," a key component for creating engaging 3D experiences. Recently,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-10 Thomas Wimmer , Michael Oechsle , Michael Niemeyer , Federico Tombari

Event cameras offer promising advantages such as high dynamic range and low latency, making them well-suited for challenging lighting conditions and fast-moving scenarios. However, reconstructing 3D scenes from raw event streams is…

Computer Vision and Pattern Recognition · Computer Science 2024-10-11 Jiaxu Wang , Junhao He , Ziyi Zhang , Mingyuan Sun , Jingkai Sun , Renjing Xu

3D Gaussian Splatting (3DGS) achieves high-fidelity rendering with fast real-time performance, but existing methods rely on offline training after full Structure-from-Motion (SfM) processing. In contrast, this work introduces Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2025-07-31 Yiwei Xu , Yifei Yu , Wentian Gan , Tengfei Wang , Zongqian Zhan , Hao Cheng , Xin Wang

Simultaneous Localization and Mapping (SLAM) is pivotal in robotics, with photorealistic scene reconstruction emerging as a key challenge. To address this, we introduce Computational Alignment for Real-Time Gaussian Splatting SLAM (CaRtGS),…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Dapeng Feng , Zhiqiang Chen , Yizhen Yin , Shipeng Zhong , Yuhua Qi , Hongbo Chen

3D Gaussian Splatting (3DGS) has gained significant attention for 3D scene reconstruction, but still suffers from complex outdoor environments, especially under adverse weather. This is because 3DGS treats the artifacts caused by adverse…

Computer Vision and Pattern Recognition · Computer Science 2025-02-13 Chenghao Qian , Yuhu Guo , Wenjing Li , Gustav Markkula

The recent surge in 4D Gaussian Splatting (4DGS) has achieved impressive dynamic scene reconstruction. While these methods demonstrate remarkable performance, the specific drivers behind such gains remain less explored, making a systematic…

Computer Vision and Pattern Recognition · Computer Science 2026-05-06 Lucas Yunkyu Lee , Soonho Kim , Youngwook Kim , Sangmin Kim , Jaesik Park

Recently, 3D Gaussian Splatting (3DGS) has emerged as an efficient approach for accurately representing scenes. However, despite its superior novel view synthesis capabilities, extracting the geometry of the scene directly from the Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Yaniv Wolf , Amit Bracha , Ron Kimmel

Temporal retiming, the ability to reconstruct and render dynamic scenes at arbitrary timestamps, is crucial for applications such as slow-motion playback, temporal editing, and post-production. However, most existing 4D Gaussian Splatting…

Computer Vision and Pattern Recognition · Computer Science 2026-05-07 Xuezhen Wang , Li Ma , Yulin Shen , Zeyu Wang , Pedro V. Sander