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Dynamic scene rendering opens new avenues in autonomous driving by enabling closed-loop simulations with photorealistic data, which is crucial for validating end-to-end algorithms. However, the complex and highly dynamic nature of traffic…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Rui Song , Chenwei Liang , Yan Xia , Walter Zimmer , Hu Cao , Holger Caesar , Andreas Festag , Alois Knoll

3D Gaussian Splatting showcases notable advancements in photo-realistic and real-time novel view synthesis. However, it faces challenges in modeling mirror reflections, which exhibit substantial appearance variations from different…

Computer Vision and Pattern Recognition · Computer Science 2024-05-21 Jiayue Liu , Xiao Tang , Freeman Cheng , Roy Yang , Zhihao Li , Jianzhuang Liu , Yi Huang , Jiaqi Lin , Shiyong Liu , Xiaofei Wu , Songcen Xu , Chun Yuan

State-of-the-art approaches for conditional human body rendering via Gaussian splatting typically focus on simple body motions captured from many views. This is often in the context of dancing or walking. However, for more complex use…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Maksym Ivashechkin , Oscar Mendez , Richard Bowden

The reconstruction of 3D objects from calibrated photographs represents a fundamental yet intricate challenge in the domains of computer graphics and vision. Although neural reconstruction approaches based on Neural Radiance Fields (NeRF)…

Computer Vision and Pattern Recognition · Computer Science 2025-02-21 Bang Du , Runfa Blark Li , Chen Du , Truong Nguyen

Recent advances in 3D Gaussian Splatting have shown promising results. Existing methods typically assume static scenes and/or multiple images with prior poses. Dynamics, sparse views, and unknown poses significantly increase the problem…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Weihang Li , Weirong Chen , Shenhan Qian , Jiajie Chen , Daniel Cremers , Haoang Li

3D Gaussian Splatting (3DGS) has shown remarkable potential for static scene reconstruction, and recent advancements have extended its application to dynamic scenes. However, the quality of reconstructions depends heavily on high-quality…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Yiren Lu , Yunlai Zhou , Disheng Liu , Tuo Liang , Yu Yin

The modeling and manipulation of 3D scenes captured from the real world are pivotal in various applications, attracting growing research interest. While previous works on editing have achieved interesting results through manipulating 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-08-15 Guan Luo , Tian-Xing Xu , Ying-Tian Liu , Xiao-Xiong Fan , Fang-Lue Zhang , Song-Hai Zhang

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

Creating 4D fields of Gaussian Splatting from images or videos is a challenging task due to its under-constrained nature. While the optimization can draw photometric reference from the input videos or be regulated by generative models,…

Computer Vision and Pattern Recognition · Computer Science 2024-05-15 Quankai Gao , Qiangeng Xu , Zhe Cao , Ben Mildenhall , Wenchao Ma , Le Chen , Danhang Tang , Ulrich Neumann

Mobile robots and IoT devices demand real-time localization and dense reconstruction under tight compute and energy budgets. While 3D Gaussian Splatting (3DGS) enables efficient dense SLAM, dynamic objects and occlusions still degrade…

Robotics · Computer Science 2026-03-02 Li Zhang , Yu-An Liu , Xijia Jiang , Conghao Huang , Danyang Li , Yanyong Zhang

Simultaneous localization and mapping (SLAM) technology has recently achieved photorealistic mapping capabilities thanks to the real-time, high-fidelity rendering enabled by 3D Gaussian Splatting (3DGS). However, due to the static…

Robotics · Computer Science 2025-12-01 Zhicong Sun , Jacqueline Lo , Jinxing Hu

Applying Gaussian Splatting to perception tasks for 3D scene understanding is becoming increasingly popular. Most existing works primarily focus on rendering 2D feature maps from novel viewpoints, which leads to an imprecise 3D language…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Hao Li , Minghan Qin , Zhengyu Zou , Diqi He , Xinhao Ji , Bohan Li , Bingquan Dai , Dingewn Zhang , Junwei Han

3D reconstruction and simulation, although interrelated, have distinct objectives: reconstruction requires a flexible 3D representation that can adapt to diverse scenes, while simulation needs a structured representation to model motion…

Computer Vision and Pattern Recognition · Computer Science 2024-11-25 Shaojie Ma , Yawei Luo , Wei Yang , Yi Yang

Recent advancements in radiance field rendering show promising results in 3D scene representation, where Gaussian splatting-based techniques emerge as state-of-the-art due to their quality and efficiency. Gaussian splatting is widely used…

Computer Vision and Pattern Recognition · Computer Science 2024-11-06 Arnab Dey , Cheng-You Lu , Andrew I. Comport , Srinath Sridhar , Chin-Teng Lin , Jean Martinet

An excellent representation is crucial for reinforcement learning (RL) performance, especially in vision-based reinforcement learning tasks. The quality of the environment representation directly influences the achievement of the learning…

Computer Vision and Pattern Recognition · Computer Science 2024-08-07 Jiaxu Wang , Qiang Zhang , Jingkai Sun , Jiahang Cao , Gang Han , Wen Zhao , Weining Zhang , Yecheng Shao , Yijie Guo , Renjing Xu

In this study, we explore the challenge of efficiently representing scenes with a constrained number of Gaussians. Our analysis shifts from traditional graphics and 2D computer vision to the perspective of point clouds, highlighting the…

Computer Vision and Pattern Recognition · Computer Science 2024-10-17 Guangchi Fang , Bing Wang

We propose ActiveSplat, an autonomous high-fidelity reconstruction system leveraging Gaussian splatting. Taking advantage of efficient and realistic rendering, the system establishes a unified framework for online mapping, viewpoint…

Robotics · Computer Science 2025-06-17 Yuetao Li , Zijia Kuang , Ting Li , Qun Hao , Zike Yan , Guyue Zhou , Shaohui Zhang

Building embodied agents capable of accomplishing arbitrary tasks is a core objective towards achieving embodied artificial general intelligence (E-AGI). While recent work has advanced such general robot policies, their training and…

Robotics · Computer Science 2025-07-30 Liu Dai , Haina Wang , Weikang Wan , Hao Su

Modeling complex rigid motion across large spatiotemporal spans remains an unresolved challenge in dynamic reconstruction. Existing paradigms are mainly confined to short-term, small-scale deformation and offer limited consideration for…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Yijun Xu , Jingrui Zhang , Yuhan Chen , Dingwen Wang , Lei Yu , Chu He

3D Gaussian Splatting (GS) has emerged as a powerful representation for high-quality scene reconstruction, offering compelling rendering quality. However, the training process of GS often suffers from slow convergence due to inefficient…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Binxiao Huang , Zhengwu Liu , Ngai Wong
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