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Related papers: K-Planes: Explicit Radiance Fields in Space, Time,…

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Neural radiance field (NeRF) attracts attention as a promising approach to reconstructing the 3D scene. As NeRF emerges, subsequent studies have been conducted to model dynamic scenes, which include motions or topological changes. However,…

Computer Vision and Pattern Recognition · Computer Science 2022-12-07 Hankyu Jang , Daeyoung Kim

We propose a novel approach to reconstruct RGB-D indoor scene based on plane primitives. Our approach takes as input a RGB-D sequence and a dense coarse mesh reconstructed from it, and generates a lightweight, low-polygonal mesh with clear…

Computer Vision and Pattern Recognition · Computer Science 2019-05-23 Chao Wang , Xiaohu Guo

We introduce a new method that efficiently computes a set of viewpoints and trajectories for high-quality 3D reconstructions in outdoor environments. Our goal is to automatically explore an unknown area, and obtain a complete 3D scan of a…

Computer Vision and Pattern Recognition · Computer Science 2018-09-19 Benjamin Hepp , Matthias Nießner , Otmar Hilliges

We present a novel way of approaching image-based 3D reconstruction based on radiance fields. The problem of volumetric reconstruction is formulated as a non-linear least-squares problem and solved explicitly without the use of neural…

Computer Vision and Pattern Recognition · Computer Science 2021-12-13 Sverker Rasmuson , Erik Sintorn , Ulf Assarsson

Creating 3D maps on robots and other mobile devices has become a reality in recent years. Online 3D reconstruction enables many exciting applications in robotics and AR/VR gaming. However, the reconstructions are noisy and generally…

Computer Vision and Pattern Recognition · Computer Science 2017-03-29 Maksym Dzitsiuk , Jürgen Sturm , Robert Maier , Lingni Ma , Daniel Cremers

We present a method, Neural Radiance Flow (NeRFlow),to learn a 4D spatial-temporal representation of a dynamic scene from a set of RGB images. Key to our approach is the use of a neural implicit representation that learns to capture the 3D…

Computer Vision and Pattern Recognition · Computer Science 2021-09-07 Yilun Du , Yinan Zhang , Hong-Xing Yu , Joshua B. Tenenbaum , Jiajun Wu

Neural Radiance Fields (NeRF) have demonstrated exceptional capabilities in reconstructing complex scenes with high fidelity. However, NeRF's view dependency can only handle low-frequency reflections. It falls short when handling complex…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 Chen Gao , Yipeng Wang , Changil Kim , Jia-Bin Huang , Johannes Kopf

Recent advances in radiance fields enable photorealistic rendering of static or dynamic 3D scenes, but still do not support explicit deformation that is used for scene manipulation or animation. In this paper, we propose a method that…

Computer Vision and Pattern Recognition · Computer Science 2022-07-26 Tianhan Xu , Tatsuya Harada

In this paper, we introduce a novel method called FRI-Net for 2D floorplan reconstruction from 3D point cloud. Existing methods typically rely on corner regression or box regression, which lack consideration for the global shapes of rooms.…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Honghao Xu , Juzhan Xu , Zeyu Huang , Pengfei Xu , Hui Huang , Ruizhen Hu

Contemporary 3D research, particularly in reconstruction and generation, heavily relies on 2D images for inputs or supervision. However, current designs for these 2D-3D mapping are memory-intensive, posing a significant bottleneck for…

Computer Vision and Pattern Recognition · Computer Science 2024-05-01 Ang Cao , Justin Johnson , Andrea Vedaldi , David Novotny

Plane arrangements are a useful tool for surface and volume modelling. However, their main drawback is poor scalability. We introduce two key novelties that enable the construction of plane arrangements for complex objects and entire…

Computational Geometry · Computer Science 2024-07-12 Raphael Sulzer , Florent Lafarge

In this paper, we propose \textit{binary radiance fields} (BiRF), a storage-efficient radiance field representation employing binary feature encoding that encodes local features using binary encoding parameters in a format of either $+1$ or…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Seungjoo Shin , Jaesik Park

We present TensoRF, a novel approach to model and reconstruct radiance fields. Unlike NeRF that purely uses MLPs, we model the radiance field of a scene as a 4D tensor, which represents a 3D voxel grid with per-voxel multi-channel features.…

Computer Vision and Pattern Recognition · Computer Science 2022-11-30 Anpei Chen , Zexiang Xu , Andreas Geiger , Jingyi Yu , Hao Su

Identifying spatially complete planar primitives from visual data is a crucial task in computer vision. Prior methods are largely restricted to either 2D segment recovery or simplifying 3D structures, even with extensive plane annotations.…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Zheng Chen , Qingan Yan , Huangying Zhan , Changjiang Cai , Xiangyu Xu , Yuzhong Huang , Weihan Wang , Ziyue Feng , Yi Xu , Lantao Liu

Neural Radiances Fields (NeRF) and their extensions have shown great success in representing 3D scenes and synthesizing novel-view images. However, most NeRF methods take in low-dynamic-range (LDR) images, which may lose details, especially…

Computer Vision and Pattern Recognition · Computer Science 2024-01-12 Guanjun Wu , Taoran Yi , Jiemin Fang , Wenyu Liu , Xinggang Wang

Interpolating missing data in k-space is essential for accelerating imaging. However, existing methods, including convolutional neural network-based deep learning, primarily exploit local predictability while overlooking the inherent global…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Chen Luo , Qiyu Jin , Taofeng Xie , Xuemei Wang , Huayu Wang , Congcong Liu , Liming Tang , Guoqing Chen , Zhuo-Xu Cui , Dong Liang

Existing works on motion deblurring either ignore the effects of depth-dependent blur or work with the assumption of a multi-layered scene wherein each layer is modeled in the form of fronto-parallel plane. In this work, we consider the…

Computer Vision and Pattern Recognition · Computer Science 2022-02-08 Kuldeep Purohit , Subeesh Vasu , M. Purnachandra Rao , A. N. Rajagopalan

Multi-channel parametric array loudspeaker (MCPAL) systems offer enhanced flexibility and promise for generating highly directional audio beams in real-world applications. However, efficient and accurate prediction of their generated sound…

Audio and Speech Processing · Electrical Eng. & Systems 2025-07-31 Tao Zhuang , Longbiao He , Feng Niu , Jia-Xin Zhong , Jing Lu

3D coverage path planning for UAVs is a crucial problem in diverse practical applications. However, existing methods have shown unsatisfactory system simplicity, computation efficiency, and path quality in large and complex scenes. To…

Robotics · Computer Science 2024-09-11 Chen Feng , Haojia Li , Mingjie Zhang , Xinyi Chen , Boyu Zhou , Shaojie Shen

Man-made environments typically comprise planar structures that exhibit numerous geometric relationships, such as parallelism, coplanarity, and orthogonality. Making full use of these relationships can considerably improve the robustness of…

Computer Vision and Pattern Recognition · Computer Science 2019-05-21 Yangbin Lin , Jialian Li , Cheng Wang , Zhonggui Chen , Zongyue Wang , Jonathan Li