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Reconstruction of rigid motion over large spatiotemporal scales remains a challenging task due to limitations in modeling paradigms, severe motion blur, and insufficient physical consistency. In this work, we propose PEGS, a framework that…

Computer Vision and Pattern Recognition · Computer Science 2025-11-24 Yijun Xu , Jingrui Zhang , Hongyi Liu , Yuhan Chen , Yuanyang Wang , Qingyao Guo , Dingwen Wang , Lei Yu , Chu He

Novel view synthesis has shown rapid progress recently, with methods capable of producing increasingly photorealistic results. 3D Gaussian Splatting has emerged as a promising method, producing high-quality renderings of scenes and enabling…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Richard Shaw , Michal Nazarczuk , Jifei Song , Arthur Moreau , Sibi Catley-Chandar , Helisa Dhamo , Eduardo Perez-Pellitero

3D Gaussian Splatting has demonstrated remarkable real-time rendering capabilities and superior visual quality in novel view synthesis for static scenes. Building upon these advantages, researchers have progressively extended 3D Gaussians…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Han Jiao , Jiakai Sun , Lei Zhao , Zhanjie Zhang , Wei Xing , Huaizhong Lin

3D Gaussian Splatting (3D-GS) technique couples 3D Gaussian primitives with differentiable rasterization to achieve high-quality novel view synthesis results while providing advanced real-time rendering performance. However, due to the flaw…

Computer Vision and Pattern Recognition · Computer Science 2024-04-17 Zongxin Ye , Wenyu Li , Sidun Liu , Peng Qiao , Yong Dou

Articulated object manipulation remains a critical challenge in robotics due to the complex kinematic constraints and the limited physical reasoning of existing methods. In this work, we introduce ArtGS, a novel framework that extends 3D…

Robotics · Computer Science 2025-07-04 Qiaojun Yu , Xibin Yuan , Yu jiang , Junting Chen , Dongzhe Zheng , Ce Hao , Yang You , Yixing Chen , Yao Mu , Liu Liu , Cewu Lu

3D object generation from a single image involves estimating the full 3D geometry and texture of unseen views from an unposed RGB image captured in the wild. Accurately reconstructing an object's complete 3D structure and texture has…

Computer Vision and Pattern Recognition · Computer Science 2024-11-21 Hritam Basak , Hadi Tabatabaee , Shreekant Gayaka , Ming-Feng Li , Xin Yang , Cheng-Hao Kuo , Arnie Sen , Min Sun , Zhaozheng Yin

3D Gaussian Splatting (3DGS) has recently unlocked real-time, high-fidelity novel view synthesis by representing scenes using explicit 3D primitives. However, traditional methods often require millions of Gaussians to capture complex…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Anh Thuan Tran , Jana Kosecka

As 3D Gaussian Splatting (3DGS) gains popularity as a 3D representation of real scenes, enabling user-friendly deformation to create novel scenes while preserving fine details from the original 3DGS has attracted significant research…

Graphics · Computer Science 2025-04-18 Yifei Tong , Runze Tian , Xiao Han , Dingyao Liu , Fenggen Yu , Yan Zhang

3D reconstruction and relighting of objects made from scattering materials present a significant challenge due to the complex light transport beneath the surface. 3D Gaussian Splatting introduced high-quality novel view synthesis at…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Jan-Niklas Dihlmann , Arjun Majumdar , Andreas Engelhardt , Raphael Braun , Hendrik P. A. Lensch

Implicit neural representation methods have shown impressive advancements in learning 3D scenes from unstructured in-the-wild photo collections but are still limited by the large computational cost of volumetric rendering. More recently, 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-04-08 Hiba Dahmani , Moussab Bennehar , Nathan Piasco , Luis Roldao , Dzmitry Tsishkou

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

Generating high-quality novel view renderings of 3D Gaussian Splatting (3DGS) in scenes featuring transient objects is challenging. We propose a novel hybrid representation, termed as HybridGS, using 2D Gaussians for transient objects per…

Computer Vision and Pattern Recognition · Computer Science 2025-03-03 Jingyu Lin , Jiaqi Gu , Lubin Fan , Bojian Wu , Yujing Lou , Renjie Chen , Ligang Liu , Jieping Ye

We present Bidirectional Gaussian Primitives, an image-based novel view synthesis technique designed to represent and render 3D objects with surface and volumetric materials under dynamic illumination. Our approach integrates light…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Zhenyuan Liu , Yu Guo , Xinyuan Li , Bernd Bickel , Ran Zhang

Articulated objects, as prevalent entities in human life, their 3D representations play crucial roles across various applications. However, achieving both high-fidelity textured surface reconstruction and dynamic generation for articulated…

Computer Vision and Pattern Recognition · Computer Science 2025-11-24 Di Wu , Liu Liu , Zhou Linli , Anran Huang , Liangtu Song , Qiaojun Yu , Qi Wu , Cewu Lu

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

Recent 4D Gaussian Splatting (4DGS) methods achieve impressive dynamic scene reconstruction but often rely on piecewise linear velocity approximations and short temporal windows. This disjointed modeling leads to severe temporal…

Computer Vision and Pattern Recognition · Computer Science 2026-04-02 Suwoong Yeom , Joonsik Nam , Seunggyu Choi , Lucas Yunkyu Lee , Sangmin Kim , Jaesik Park , Joonsoo Kim , Kugjin Yun , Kyeongbo Kong , Sukju Kang

Real-time rendering of dynamic scenes with view-dependent effects remains a fundamental challenge in computer graphics. While recent advances in Gaussian Splatting have shown promising results separately handling dynamic scenes (4DGS) and…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Zhongpai Gao , Benjamin Planche , Meng Zheng , Anwesa Choudhuri , Terrence Chen , Ziyan Wu

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…

Implicit neural representation has paved the way for new approaches to dynamic scene reconstruction and rendering. Nonetheless, cutting-edge dynamic neural rendering methods rely heavily on these implicit representations, which frequently…

Computer Vision and Pattern Recognition · Computer Science 2023-11-22 Ziyi Yang , Xinyu Gao , Wen Zhou , Shaohui Jiao , Yuqing Zhang , Xiaogang Jin

We propose a novel framework that enhances non-rigid 3D model deformations by bridging mesh representations with 3D Gaussian splatting. While traditional Gaussian splatting delivers fast, real-time radiance-field rendering, its post-editing…

Graphics · Computer Science 2025-07-10 Wijayathunga W. M. R. D. B