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Latent scene representation plays a significant role in training reinforcement learning (RL) agents. To obtain good latent vectors describing the scenes, recent works incorporate the 3D-aware latent-conditioned NeRF pipeline into scene…

Robotics · Computer Science 2024-09-30 Jiaxu Wang , Ziyi Zhang , Qiang Zhang , Jia Li , Jingkai Sun , Mingyuan Sun , Junhao He , Renjing Xu

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

In-the-wild photo collections often contain limited volumes of imagery and exhibit multiple appearances, e.g., taken at different times of day or seasons, posing significant challenges to scene reconstruction and novel view synthesis.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-27 Deming Li , Kaiwen Jiang , Yutao Tang , Ravi Ramamoorthi , Rama Chellappa , Cheng Peng

Reconstructing and predicting dynamic 3D scenes from multi-view videos is a foundational task for robotics, AR/VR, and digital twins. Recent physics-informed Gaussian Splatting methods achieve impressive future frame extrapolation but lack…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Denis Gridusov , Maxim Popov , Sergey Kolyubin

Digitizing 3D static scenes and 4D dynamic events from multi-view images has long been a challenge in computer vision and graphics. Recently, 3D Gaussian Splatting (3DGS) has emerged as a practical and scalable reconstruction method,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-18 Marko Mihajlovic , Sergey Prokudin , Siyu Tang , Robert Maier , Federica Bogo , Tony Tung , Edmond Boyer

Recently, 3D Gaussian splatting (3D-GS) has gained popularity in novel-view scene synthesis. It addresses the challenges of lengthy training times and slow rendering speeds associated with Neural Radiance Fields (NeRFs). Through rapid,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-27 Sharath Girish , Kamal Gupta , Abhinav Shrivastava

Differentiable rendering techniques have recently shown promising results for free-viewpoint video synthesis of characters. However, such methods, either Gaussian Splatting or neural implicit rendering, typically necessitate per-subject…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Boyao Zhou , Shunyuan Zheng , Hanzhang Tu , Ruizhi Shao , Boning Liu , Shengping Zhang , Liqiang Nie , Yebin Liu

Generating realistic 3D scenes from text is crucial for immersive applications like VR, AR, and gaming. While text-driven approaches promise efficiency, existing methods suffer from limited 3D-text data and inconsistent multi-view…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Xin Zhang , Shen Chen , Jiale Zhou , Lei Li

The recently developed Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) have shown encouraging and impressive results for visual SLAM. However, most representative methods require RGBD sensors and are only available for indoor…

Computer Vision and Pattern Recognition · Computer Science 2025-05-16 Zhe Xin , Chenyang Wu , Penghui Huang , Yanyong Zhang , Yinian Mao , Guoquan Huang

Recent advances in 3D Gaussian Splatting (3DGS) have enabled Simultaneous Localization and Mapping (SLAM) systems to build photorealistic maps. However, these maps lack the open-vocabulary semantic understanding required for advanced…

Computer Vision and Pattern Recognition · Computer Science 2025-11-21 Sibaek Lee , Seongbo Ha , Kyeongsu Kang , Joonyeol Choi , Seungjun Tak , Hyeonwoo Yu

3D Gaussian Splatting (3DGS) has emerged as a powerful representation for neural scene reconstruction, offering high-quality novel view synthesis while maintaining computational efficiency. In this paper, we extend the capabilities of 3DGS…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Jens Piekenbrinck , Christian Schmidt , Alexander Hermans , Narunas Vaskevicius , Timm Linder , Bastian Leibe

Learning 4D language fields to enable time-sensitive, open-ended language queries in dynamic scenes is essential for many real-world applications. While LangSplat successfully grounds CLIP features into 3D Gaussian representations,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Wanhua Li , Renping Zhou , Jiawei Zhou , Yingwei Song , Johannes Herter , Minghan Qin , Gao Huang , Hanspeter Pfister

3D Gaussian Splatting is emerging as a state-of-the-art technique in novel view synthesis, recognized for its impressive balance between visual quality, speed, and rendering efficiency. However, reliance on third-degree spherical harmonics…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Yiwen Wang , Siyuan Chen , Ran Yi

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

We introduce Ilov3Splat, a novel framework for instance-level open-vocabulary 3D scene understanding built on 3D Gaussian Splatting (3D-GS). Most prior work depends on 2D rendering-based matching or point-level semantic association, which…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Binh Long Nguyen , Kien Nguyen , Sridha Sridharan , Clinton Fookes , Peyman Moghadam

Semantic-aware 3D scene reconstruction is essential for autonomous robots to perform complex interactions. Semantic SLAM, an online approach, integrates pose tracking, geometric reconstruction, and semantic mapping into a unified framework,…

Robotics · Computer Science 2025-05-20 Zuxing Lu , Xin Yuan , Shaowen Yang , Jingyu Liu , Changyin Sun

Achieving unified 3D perception and reasoning across tasks such as segmentation, retrieval, and relation understanding remains challenging, as existing methods are either object-centric or rely on costly training for inter-object reasoning.…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Yaxu Xie , Abdalla Arafa , Alireza Javanmardi , Christen Millerdurai , Jia Cheng Hu , Shaoxiang Wang , Alain Pagani , Didier Stricker

Advancements in 3D rendering like Gaussian Splatting (GS) allow novel view synthesis and real-time rendering in virtual reality (VR). However, GS-created 3D environments are often difficult to edit. For scene enhancement or to incorporate…

Computer Vision and Pattern Recognition · Computer Science 2024-09-25 Hannah Schieber , Jacob Young , Tobias Langlotz , Stefanie Zollmann , Daniel Roth

3D Gaussian Splatting (3DGS) enables high-quality rendering of 3D scenes and is getting increasing adoption in domains like autonomous driving and embodied intelligence. However, 3DGS still faces major efficiency challenges when faced with…

Hardware Architecture · Computer Science 2025-07-31 Linye Wei , Jiajun Tang , Fan Fei , Boxin Shi , Runsheng Wang , Meng Li

Novel view synthesis for dynamic scenes is still a challenging problem in computer vision and graphics. Recently, Gaussian splatting has emerged as a robust technique to represent static scenes and enable high-quality and real-time novel…

Computer Vision and Pattern Recognition · Computer Science 2024-04-15 Yi-Hua Huang , Yang-Tian Sun , Ziyi Yang , Xiaoyang Lyu , Yan-Pei Cao , Xiaojuan Qi