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3D Gaussian splatting (3DGS) has demonstrated impressive performance in synthesizing high-fidelity novel views. Nonetheless, its effectiveness critically depends on the quality of the initialized point cloud. Specifically, achieving uniform…

Computer Vision and Pattern Recognition · Computer Science 2025-10-13 Yikang Zhang , Rui Fan

Although 3D Gaussian Splatting (3D-GS) achieves efficient rendering for novel view synthesis, extending it to dynamic scenes still results in substantial memory overhead from replicating Gaussians across frames. To address this challenge,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Chun-Tin Wu , Jun-Cheng Chen

The advent of generative radiance fields has significantly promoted the development of 3D-aware image synthesis. The cumulative rendering process in radiance fields makes training these generative models much easier since gradients are…

Computer Vision and Pattern Recognition · Computer Science 2021-11-02 Xudong Xu , Xingang Pan , Dahua Lin , Bo Dai

In this paper, we propose OccTENS, a generative occupancy world model that enables controllable, high-fidelity long-term occupancy generation while maintaining computational efficiency. Different from visual generation, the occupancy world…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Bu Jin , Songen Gu , Xiaotao Hu , Yupeng Zheng , Xiaoyang Guo , Qian Zhang , Xiaoxiao Long , Wei Yin

State-of-the-art navigation methods leverage a spatial memory to generalize to new environments, but their occupancy maps are limited to capturing the geometric structures directly observed by the agent. We propose occupancy anticipation,…

Computer Vision and Pattern Recognition · Computer Science 2020-08-26 Santhosh K. Ramakrishnan , Ziad Al-Halah , Kristen Grauman

3D Gaussian Splatting (3DGS) effectively synthesizes novel views through its flexible representation, yet fails to accurately reconstruct scene geometry. While modern variants like PGSR introduce additional losses to ensure proper depth and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Zhentao Huang , Di Wu , Zhenbang He , Minglun Gong

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

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

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

Simultaneous localization and mapping is essential for position tracking and scene understanding. 3D Gaussian-based map representations enable photorealistic reconstruction and real-time rendering of scenes using multiple posed cameras. We…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Lisong C. Sun , Neel P. Bhatt , Jonathan C. Liu , Zhiwen Fan , Zhangyang Wang , Todd E. Humphreys , Ufuk Topcu

While 3D object bounding box (bbox) representation has been widely used in autonomous driving perception, it lacks the ability to capture the precise details of an object's intrinsic geometry. Recently, occupancy has emerged as a promising…

Computer Vision and Pattern Recognition · Computer Science 2024-12-09 Chaoda Zheng , Feng Wang , Naiyan Wang , Shuguang Cui , Zhen Li

Neural Radiance Fields (NeRFs) have demonstrated remarkable potential in capturing complex 3D scenes with high fidelity. However, one persistent challenge that hinders the widespread adoption of NeRFs is the computational bottleneck due to…

Computer Vision and Pattern Recognition · Computer Science 2024-02-16 Joo Chan Lee , Daniel Rho , Xiangyu Sun , Jong Hwan Ko , Eunbyung Park

Recent studies in Radiance Fields have paved the robust way for novel view synthesis with their photorealistic rendering quality. Nevertheless, they usually employ neural networks and volumetric rendering, which are costly to train and…

Computer Vision and Pattern Recognition · Computer Science 2024-09-25 Byeonghyeon Lee , Howoong Lee , Xiangyu Sun , Usman Ali , Eunbyung Park

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

The advent of neural 3D Gaussians has recently brought about a revolution in the field of neural rendering, facilitating the generation of high-quality renderings at real-time speeds. However, the explicit and discrete representation…

Computer Vision and Pattern Recognition · Computer Science 2023-12-01 Yingwenqi Jiang , Jiadong Tu , Yuan Liu , Xifeng Gao , Xiaoxiao Long , Wenping Wang , Yuexin Ma

3D Gaussian Splatting (3DGS) has demonstrated impressive novel view synthesis performance. While conventional methods require per-scene optimization, more recently several feed-forward methods have been proposed to generate pixel-aligned…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Shengjun Zhang , Xin Fei , Fangfu Liu , Haixu Song , Yueqi Duan

This paper introduces InverseMatrixVT3D, an efficient method for transforming multi-view image features into 3D feature volumes for 3D semantic occupancy prediction. Existing methods for constructing 3D volumes often rely on depth…

Computer Vision and Pattern Recognition · Computer Science 2024-04-30 Zhenxing Ming , Julie Stephany Berrio , Mao Shan , Stewart Worrall

Novel view synthesis has seen major advances in recent years, with 3D Gaussian splatting offering an excellent level of visual quality, fast training and real-time rendering. However, the resources needed for training and rendering…

Computer Vision and Pattern Recognition · Computer Science 2024-06-19 Bernhard Kerbl , Andréas Meuleman , Georgios Kopanas , Michael Wimmer , Alexandre Lanvin , George Drettakis

This work presents a novel pipeline to recover the 3D structure of an unknown target spacecraft from a sequence of images captured during Rendezvous and Proximity Operations (RPO) in space. The target's geometry and appearance are…

Computer Vision and Pattern Recognition · Computer Science 2026-01-01 Tae Ha Park , Simone D'Amico

3D Gaussian Splatting (3DGS) has become increasingly popular in 3D scene reconstruction for its high visual accuracy. However, uncertainty estimation of 3DGS scenes remains underexplored and is crucial to downstream tasks such as asset…

Computer Vision and Pattern Recognition · Computer Science 2025-04-11 Chenyu Han , Corentin Dumery