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Processing large indoor scenes is a challenging task, as scan registration and camera trajectory estimation methods accumulate errors across time. As a result, the quality of reconstructed scans is insufficient for some applications, such…

Computer Vision and Pattern Recognition · Computer Science 2022-10-11 Anna Sokolova , Filipp Nikitin , Anna Vorontsova , Anton Konushin

This paper addresses the limitations of neural rendering-based multi-view surface reconstruction methods, which require an additional mesh extraction step that is inconvenient and would produce poor-quality surfaces with mesh aliasing,…

Computer Vision and Pattern Recognition · Computer Science 2025-08-26 Qitong Zhang , Jieqing Feng

We present a new framework to reconstruct holistic 3D indoor scenes including both room background and indoor objects from single-view images. Existing methods can only produce 3D shapes of indoor objects with limited geometry quality…

Computer Vision and Pattern Recognition · Computer Science 2022-08-09 Haolin Liu , Yujian Zheng , Guanying Chen , Shuguang Cui , Xiaoguang Han

Acquiring 3D geometry of real world objects has various applications in 3D digitization, such as navigation and content generation in virtual environments. Image remains one of the most popular media for such visual tasks due to its…

Computer Vision and Pattern Recognition · Computer Science 2017-01-26 Shuai Du , Youyi Zheng

Reconstructing dynamic 4D scenes from monocular videos is a fundamental yet challenging task. While recent 3D foundation models provide strong geometric priors, their performance significantly degrades in dynamic environments. This…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Ying Zang , Xuanyi Liu , Yidong Han , Deyi Ji , Chaotao Ding , Yuanqi Hu , Qi Zhu , Xuanfu Li , Jin Ma , Lingyun Sun , Tianrun Chen , Lanyun Zhu

We present a simple yet effective general-purpose framework for modeling 3D shapes by leveraging recent advances in 2D image generation using CNNs. Using just a single depth image of the object, we can output a dense multi-view depth map…

Computer Vision and Pattern Recognition · Computer Science 2020-09-08 Kamal Gupta , Susmija Jabbireddy , Ketul Shah , Abhinav Shrivastava , Matthias Zwicker

Reconstructing detailed 3D scenes from single-view images remains a challenging task due to limitations in existing approaches, which primarily focus on geometric shape recovery, overlooking object appearances and fine shape details. To…

Computer Vision and Pattern Recognition · Computer Science 2023-11-02 Yixin Chen , Junfeng Ni , Nan Jiang , Yaowei Zhang , Yixin Zhu , Siyuan Huang

Compressive imaging is an emerging application of compressed sensing, devoted to acquisition, encoding and reconstruction of images using random projections as measurements. In this paper we propose a novel method to provide a scalable…

Information Theory · Computer Science 2013-10-07 Diego Valsesia , Enrico Magli

Image inpainting is a technique used to restore missing or damaged regions of an image. Traditional methods primarily utilize information from adjacent pixels for reconstructing missing areas, while they struggle to preserve complex details…

Computer Vision and Pattern Recognition · Computer Science 2025-04-25 Junyan Zhang , Yan Li , Mengxiao Geng , Liu Shi , Qiegen Liu

In this work, we use multi-view aerial images to reconstruct the geometry, lighting, and material of facades using neural signed distance fields (SDFs). Without the requirement of complex equipment, our method only takes simple RGB images…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Zixuan Xie , Rengan Xie , Rong Li , Kai Huang , Pengju Qiao , Jingsen Zhu , Xu Yin , Qi Ye , Wei Hua , Yuchi Huo , Hujun Bao

How to use multiple optical satellite images to recover the 3D scene structure is a challenging and important problem in the remote sensing field. Most existing methods in literature have been explored based on the classical RPC (rational…

Computer Vision and Pattern Recognition · Computer Science 2022-12-07 Pinhe Wang , Limin Shi , Bao Chen , Zhanyi Hu , Qiulei Dong , Jianzhong Qiao

Joint camera pose and dense geometry estimation from a set of images or a monocular video remains a challenging problem due to its computational complexity and inherent visual ambiguities. Most dense incremental reconstruction systems…

Computer Vision and Pattern Recognition · Computer Science 2024-04-18 Kirill Mazur , Gwangbin Bae , Andrew J. Davison

Reconstructing dynamic 3D scenes from monocular video remains fundamentally challenging due to the need to jointly infer motion, structure, and appearance from limited observations. Existing dynamic scene reconstruction methods based on…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Jiahui Li , Shengeng Tang , Jingxuan He , Gang Huang , Zhangye Wang , Yantao Pan , Lechao Cheng

Extracting planes from a 3D scene is useful for downstream tasks in robotics and augmented reality. In this paper we tackle the problem of estimating the planar surfaces in a scene from posed images. Our first finding is that a surprisingly…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Jamie Watson , Filippo Aleotti , Mohamed Sayed , Zawar Qureshi , Oisin Mac Aodha , Gabriel Brostow , Michael Firman , Sara Vicente

Three-dimensional reconstruction in scenes with extreme depth variations remains challenging due to inconsistent supervisory signals between near-field and far-field regions. Existing methods fail to simultaneously address inaccurate depth…

Computer Vision and Pattern Recognition · Computer Science 2025-11-14 Yu Deng , Baozhu Zhao , Junyan Su , Xiaohan Zhang , Qi Liu

Despite significant progress in monocular depth estimation in the wild, recent state-of-the-art methods cannot be used to recover accurate 3D scene shape due to an unknown depth shift induced by shift-invariant reconstruction losses used in…

Computer Vision and Pattern Recognition · Computer Science 2020-12-18 Wei Yin , Jianming Zhang , Oliver Wang , Simon Niklaus , Long Mai , Simon Chen , Chunhua Shen

Removing noise from images is a challenging and fundamental problem in the field of computer vision. Images captured by modern cameras are inevitably degraded by noise which limits the accuracy of any quantitative measurements on those…

Computer Vision and Pattern Recognition · Computer Science 2023-07-13 Nikhil Verma , Deepkamal Kaur , Lydia Chau

Recovering the missing regions of an image is a task that is called image inpainting. Depending on the shape of missing areas, different methods are presented in the literature. One of the challenges of this problem is extracting features…

Computer Vision and Pattern Recognition · Computer Science 2020-01-13 Ghazale Ghorbanzade , Zahra Nabizadeh , Nader Karimi , Shadrokh Samavi

This paper presents a pixel-by-pixel spatial prediction method for lossless intra coding within High Efficiency Video Coding (HEVC). A well-known previous pixel-by-pixel spatial prediction method uses only two neighboring pixels for…

Multimedia · Computer Science 2016-01-19 Saeed R. Alvar , Fatih Kamisli

Presence of haze in images obscures underlying information, which is undesirable in applications requiring accurate environment information. To recover such an image, a dehazing algorithm should localize and recover affected regions while…

Computer Vision and Pattern Recognition · Computer Science 2021-01-27 Pranjay Shyam , Kuk-Jin Yoon , Kyung-Soo Kim
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