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The use of multi-view images acquired by a 360-degree camera can reconstruct a 3D space with a wide area. There are 3D reconstruction methods from equirectangular images based on NeRF and 3DGS, as well as Novel View Synthesis (NVS) methods.…

Computer Vision and Pattern Recognition · Computer Science 2025-06-02 Shintaro Ito , Natsuki Takama , Koichi Ito , Hwann-Tzong Chen , Takafumi Aoki

Omnidirectional image (ODI) data is captured with a 360x180 field-of-view, which is much wider than the pinhole cameras and contains richer spatial information than the conventional planar images. Accordingly, omnidirectional vision has…

Computer Vision and Pattern Recognition · Computer Science 2022-05-25 Hao Ai , Zidong Cao , Jinjing Zhu , Haotian Bai , Yucheng Chen , Lin Wang

This paper proposes a method to reconstruct the neural radiance field with equirectangular omnidirectional images. Implicit neural scene representation with a radiance field can reconstruct the 3D shape of a scene continuously within a…

Computer Vision and Pattern Recognition · Computer Science 2022-08-15 Qiaoge Li , Itsuki Ueda , Chun Xie , Hidehiko Shishido , Itaru Kitahara

3D object inpainting is commonly achieved via multi-view 2D image completion, yet independently inpainted views often suffer from cross-view inconsistencies, leading to blurred textures, geometric discontinuities, and visual artifacts in…

Computer Vision and Pattern Recognition · Computer Science 2026-05-28 Haitang Feng , Xinkai Chen , Jie Liu , Jie Tang , Gangshan Wu , Beiqi Chen , Jianhuang Lai , Guangcong Wang

While feed-forward 3D reconstruction models have advanced rapidly, they still exhibit degraded performance on panoramas due to spherical distortions. Moreover, existing panoramic 3D datasets are predominantly collected with 360 cameras…

Computer Vision and Pattern Recognition · Computer Science 2026-04-27 Jing Ou , Zidong Cao , Yinrui Ren , Zhuoxiao Li , Jinjing Zhu , Tongyan Hua , Shuai Zhang , Hui Xiong , Wufan Zhao

3D scene understanding for robotic applications exhibits a unique set of requirements including real-time inference, object-centric latent representation learning, accurate 6D pose estimation and 3D reconstruction of objects. Current…

Robotics · Computer Science 2024-02-27 Yizhe Wu , Haitz Sáez de Ocáriz Borde , Jack Collins , Oiwi Parker Jones , Ingmar Posner

3D dense reconstruction refers to the process of obtaining the complete shape and texture features of 3D objects from 2D planar images. 3D reconstruction is an important and extensively studied problem, but it is far from being solved. This…

Computer Vision and Pattern Recognition · Computer Science 2023-04-20 Yangming Li

The problem of 3D reconstruction from posed images is undergoing a fundamental transformation, driven by continuous advances in 3D Gaussian Splatting (3DGS). By modeling scenes explicitly as collections of 3D Gaussians, 3DGS enables…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Vitor Pereira Matias , Daniel Perazzo , Vinicius Silva , Alberto Raposo , Luiz Velho , Afonso Paiva , Tiago Novello

With the advent of deep neural networks, learning-based approaches for 3D reconstruction have gained popularity. However, unlike for images, in 3D there is no canonical representation which is both computationally and memory efficient yet…

Computer Vision and Pattern Recognition · Computer Science 2019-05-01 Lars Mescheder , Michael Oechsle , Michael Niemeyer , Sebastian Nowozin , Andreas Geiger

Recent advances in 3D reconstruction and neural rendering,particularly 3D Gaussian Splatting, make it feasible and simple to edit 3D scenes and re-render them as highly realistic images. Therefore, security concerns arise regarding the…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Davide Di Nucci , Riccardo Catalini , Guido Borghi , Roberto Vezzani

3D reconstruction, which aims to recover the dense three-dimensional structure of a scene, is a cornerstone technology for numerous applications, including augmented/virtual reality, autonomous driving, and robotics. While traditional…

Computer Vision and Pattern Recognition · Computer Science 2025-07-14 Wei Zhang , Yihang Wu , Songhua Li , Wenjie Ma , Xin Ma , Qiang Li , Qi Wang

Neural rendering methods such as Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) have achieved significant progress in photorealistic 3D scene reconstruction and novel view synthesis. However, most existing models assume…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Weeyoung Kwon , Jeahun Sung , Minkyu Jeon , Chanho Eom , Jihyong Oh

Traditional computer graphics rendering pipeline is designed for procedurally generating 2D quality images from 3D shapes with high performance. The non-differentiability due to discrete operations such as visibility computation makes it…

Computer Vision and Pattern Recognition · Computer Science 2019-04-10 Thu Nguyen-Phuoc , Chuan Li , Stephen Balaban , Yong-Liang Yang

Omnidirectional images (ODIs) are commonly used in real-world visual tasks, and high-resolution ODIs help improve the performance of related visual tasks. Most existing super-resolution methods for ODIs use end-to-end learning strategies,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-18 Runyi Li , Xuhan Sheng , Weiqi Li , Jian Zhang

Lidar technology has evolved significantly over the last decade, with higher resolution, better accuracy, and lower cost devices available today. In addition, new scanning modalities and novel sensor technologies have emerged in recent…

Robotics · Computer Science 2022-03-08 Qingqing Li , Xianjia Yu , Jorge Peña Queralta , Tomi Westerlund

We present ObSuRF, a method which turns a single image of a scene into a 3D model represented as a set of Neural Radiance Fields (NeRFs), with each NeRF corresponding to a different object. A single forward pass of an encoder network…

Computer Vision and Pattern Recognition · Computer Science 2021-04-05 Karl Stelzner , Kristian Kersting , Adam R. Kosiorek

We present AMB3R, a multi-view feed-forward model for dense 3D reconstruction on a metric-scale that addresses diverse 3D vision tasks. The key idea is to leverage a sparse, yet compact, volumetric scene representation as our backend,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Hengyi Wang , Lourdes Agapito

In visual computing, 3D geometry is represented in many different forms including meshes, point clouds, voxel grids, level sets, and depth images. Each representation is suited for different tasks thus making the transformation of one…

Computer Vision and Pattern Recognition · Computer Science 2022-09-02 Trevor Houchens , Cheng-You Lu , Shivam Duggal , Rao Fu , Srinath Sridhar

Underwater scene reconstruction is essential for immersive exploration of aquatic environments, yet remains challenging due to complex participating-media effects such as absorption and scattering, as well as the limited field of view (FoV)…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Jiangbei Hu , Weichao Song , Shibo Yu , Mohan Wang , Zihan Yi , Rui Wu , Mingkang Xiang , Na Lei , Shengfa Wang , Zhongxuan Luo , Ying He

3D object reconstruction is important for semantic scene understanding. It is challenging to reconstruct detailed 3D shapes from monocular images directly due to a lack of depth information, occlusion and noise. Most current methods…

Computer Vision and Pattern Recognition · Computer Science 2023-11-07 Ziwei Liao , Steven L. Waslander