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Recent advancements in 3D reconstruction methods and vision-language models have propelled the development of multi-modal 3D scene understanding, which has vital applications in robotics, autonomous driving, and virtual/augmented reality.…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Qucheng Peng , Benjamin Planche , Zhongpai Gao , Meng Zheng , Anwesa Choudhuri , Terrence Chen , Chen Chen , Ziyan Wu

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 scene reconstruction and rendering are core tasks in computer vision, with applications spanning industrial monitoring, robotics, and autonomous driving. Recent advances in 3D Gaussian Splatting (GS) and its variants have achieved…

Computer Vision and Pattern Recognition · Computer Science 2026-02-20 Chi-Shiang Gau , Konstantinos D. Polyzos , Athanasios Bacharis , Saketh Madhuvarasu , Tara Javidi

Recent advancements in 3D reconstruction coupled with neural rendering techniques have greatly improved the creation of photo-realistic 3D scenes, influencing both academic research and industry applications. The technique of 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Zexu Huang , Min Xu , Stuart Perry

Recent advancements in 3D scene understanding have made significant strides in enabling interaction with scenes using open-vocabulary queries, particularly for VR/AR and robotic applications. Nevertheless, existing methods are hindered by…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Dianyi Yang , Xihan Wang , Yu Gao , Shiyang Liu , Bohan Ren , Yufeng Yue , Yi Yang

Recent advances in Gaussian Splatting based 3D scene representation have shown two major trends: semantics-oriented approaches that focus on high-level understanding but lack explicit 3D geometry modeling, and structure-oriented approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Yuhang Ming , Chenxin Fang , Xingyuan Yu , Fan Zhang , Weichen Dai , Wanzeng Kong , Guofeng Zhang

Scene representations using 3D Gaussian primitives have produced excellent results in modeling the appearance of static and dynamic 3D scenes. Many graphics applications, however, demand the ability to manipulate both the appearance and the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Ri-Zhao Qiu , Ge Yang , Weijia Zeng , Xiaolong Wang

The emergence of 3D Gaussian Splatting (3DGS) has greatly accelerated the rendering speed of novel view synthesis. Unlike neural implicit representations like Neural Radiance Fields (NeRF) that represent a 3D scene with position and…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Tong Wu , Yu-Jie Yuan , Ling-Xiao Zhang , Jie Yang , Yan-Pei Cao , Ling-Qi Yan , Lin Gao

Recent advancements in Generalizable Gaussian Splatting have enabled robust 3D reconstruction from sparse input views by utilizing feed-forward Gaussian Splatting models, achieving superior cross-scene generalization. However, while many…

Computer Vision and Pattern Recognition · Computer Science 2025-08-22 Zhicong Wu , Hongbin Xu , Gang Xu , Ping Nie , Zhixin Yan , Jinkai Zheng , Liangqiong Qu , Ming Li , Liqiang Nie

3D Gaussian Splatting (3DGS) serves as a highly performant and efficient encoding of scene geometry, appearance, and semantics. Moreover, grounding language in 3D scenes has proven to be an effective strategy for 3D scene understanding.…

Computer Vision and Pattern Recognition · Computer Science 2026-01-27 Mengjiao Ma , Qi Ma , Yue Li , Jiahuan Cheng , Runyi Yang , Bin Ren , Nikola Popovic , Mingqiang Wei , Nicu Sebe , Luc Van Gool , Theo Gevers , Martin R. Oswald , Danda Pani Paudel

Recognizing arbitrary or previously unseen categories is essential for comprehensive real-world 3D scene understanding. Currently, all existing methods rely on 2D or textual modalities during training or together at inference. This…

Computer Vision and Pattern Recognition · Computer Science 2025-06-04 Yue Li , Qi Ma , Runyi Yang , Huapeng Li , Mengjiao Ma , Bin Ren , Nikola Popovic , Nicu Sebe , Ender Konukoglu , Theo Gevers , Luc Van Gool , Martin R. Oswald , Danda Pani Paudel

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

Accurately reconstructing a 3D scene including explicit geometry information is both attractive and challenging. Geometry reconstruction can benefit from incorporating differentiable appearance models, such as Neural Radiance Fields and 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Ancheng Lin , Yusheng Xiang , Paul Kennedy , Jun Li

The integration of aerial and ground images has been a promising solution in 3D modeling of complex scenes, which is seriously restricted by finding reliable correspondences. The primary contribution of this study is a feature matching…

Computer Vision and Pattern Recognition · Computer Science 2025-09-25 Jiangxue Yu , Hui Wang , San Jiang , Xing Zhang , Dejin Zhang , Qingquan Li

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

Three-dimensional Gaussian Splatting (3DGS) has recently emerged as an efficient representation for novel-view synthesis, achieving impressive visual quality. However, in scenes dominated by large and low-texture regions, common in indoor…

Computer Vision and Pattern Recognition · Computer Science 2025-10-29 Xirui Jin , Renbiao Jin , Boying Li , Danping Zou , Wenxian Yu

Given that visual foundation models (VFMs) are trained on extensive datasets but often limited to 2D images, a natural question arises: how well do they understand the 3D world? With the differences in architecture and training protocols…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Yue Chen , Xingyu Chen , Anpei Chen , Gerard Pons-Moll , Yuliang Xiu

3D Gaussian Splatting (3DGS) has emerged as a powerful approach for 3D scene reconstruction using 3D Gaussians. However, neither the centers nor surfaces of the Gaussians are accurately aligned to the object surface, complicating their…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Miriam Jäger , Markus Hillemann , Boris Jutzi

Recent advances in leveraging large-scale Internet photo collections for 3D reconstruction have enabled immersive virtual exploration of landmarks and historic sites worldwide. However, little attention has been given to the immersive…

Graphics · Computer Science 2025-08-06 Yuze Wang , Yue Qi

Existing 3DGS methods effectively render high-quality novel views in clear-day scenes. However, they struggle with night scenes, particularly in glow regions, due to the lack of structural features such as textures and edges, which are key…

Computer Vision and Pattern Recognition · Computer Science 2026-05-25 Beibei Lin , Xiao Cao , Jingyuan Guo , Robby T. Tan