English
Related papers

Related papers: SARe: Structure-Aware Large-Scale 3D Fragment Reas…

200 papers

3D reassembly is a challenging spatial intelligence task with broad applications across scientific domains. While large-scale synthetic datasets have fueled promising learning-based approaches, their generalizability to different domains is…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Sihang Li , Zeyu Jiang , Grace Chen , Chenyang Xu , Siqi Tan , Xue Wang , Irving Fang , Kristof Zyskowski , Shannon P. McPherron , Radu Iovita , Chen Feng , Jing Zhang

To translate synthetic aperture radar (SAR) image into interpretable forms for human understanding is the ultimate goal of SAR advanced information retrieval. Existing methods mainly focus on 3D surface reconstruction or local geometric…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Ziyu Yue , Ruixi You , Feng Xu

X-ray images ease the diagnosis and treatment process due to their rapid imaging speed and high resolution. However, due to the projection process of X-ray imaging, much spatial information has been lost. To accurately provide efficient…

Image and Video Processing · Electrical Eng. & Systems 2024-08-06 Lixing Tan , Shuang Song , Yaofeng He , Kangneng Zhou , Tong Lu , Ruoxiu Xiao

Most existing 3D assembly methods treat the problem as pure pose estimation, rearranging observed parts via rigid transformations. In contrast, human assembly naturally couples structural reasoning with holistic shape inference. Inspired by…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Zeyu Jiang , Sihang Li , Siqi Tan , Chenyang Xu , Juexiao Zhang , Julia Galway-Witham , Xue Wang , Scott A. Williams , Radu Iovita , Chen Feng , Jing Zhang

Single-view 3D shape retrieval is a fundamental yet challenging task that is increasingly important with the growth of available 3D data. Existing approaches largely fall into two categories: those using contrastive learning to map point…

Computer Vision and Pattern Recognition · Computer Science 2026-04-30 Jiaxin Shi , Guofeng Zhang , Wufei Ma , Naifu Liang , Adam Kortylewski , Alan Yuille

SAR (Synthetic Aperture Radar) tomography reconstructs 3-D volumes from stacks of SAR images. High-resolution satellites such as TerraSAR-X provide images that can be combined to produce 3-D models. In urban areas, sparsity priors are…

Computer Vision and Pattern Recognition · Computer Science 2021-03-15 Clément Rambour , Loïc Denis , Florence Tupin , Hélène Oriot , Yue Huang , Laurent Ferro-Famil

Neural surface reconstruction (NSR) has recently shown strong potential for urban 3D reconstruction from multi-view aerial imagery. However, existing NSR methods often suffer from geometric ambiguity and instability, particularly under…

Computer Vision and Pattern Recognition · Computer Science 2026-01-30 Da Li , Chen Yao , Tong Mao , Jiacheng Bao , Houjun Sun

Geometric fracture assembly presents a challenging practical task in archaeology and 3D computer vision. Previous methods have focused solely on assembling fragments based on semantic information, which has limited the quantity of objects…

Computer Vision and Pattern Recognition · Computer Science 2024-01-17 Ruiyuan Zhang , Jiaxiang Liu , Zexi Li , Hao Dong , Jie Fu , Chao Wu

We introduce a new problem of retrieving 3D models that are deformable to a given query shape and present a novel deep deformation-aware embedding to solve this retrieval task. 3D model retrieval is a fundamental operation for recovering a…

Computer Vision and Pattern Recognition · Computer Science 2020-08-03 Mikaela Angelina Uy , Jingwei Huang , Minhyuk Sung , Tolga Birdal , Leonidas Guibas

Composed image retrieval (CIR) is a vision language task that retrieves a target image using a reference image and modification text, enabling intuitive specification of desired changes. While effectively fusing visual and textual…

Computer Vision and Pattern Recognition · Computer Science 2025-07-18 Jeong-Woo Park , Young-Eun Kim , Seong-Whan Lee

We propose a semantic-aware neural reconstruction method to generate 3D high-fidelity models from sparse images. To tackle the challenge of severe radiance ambiguity caused by mismatched features in sparse input, we enrich neural implicit…

Computer Vision and Pattern Recognition · Computer Science 2025-08-27 Bo Xu , Yuhu Guo , Yuchao Wang , Wenting Wang , Yeung Yam , Charlie C. L. Wang , Xinyi Le

This paper introduces a new approach for the automated reconstruction - reassembly of fragmented objects having one surface near to plane, on the basis of the 3D representation of their constituent fragments. The whole process starts by 3D…

We explore the task of zero-shot semantic segmentation of 3D shapes by using large-scale off-the-shelf 2D image recognition models. Surprisingly, we find that modern zero-shot 2D object detectors are better suited for this task than…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Ahmed Abdelreheem , Ivan Skorokhodov , Maks Ovsjanikov , Peter Wonka

Reconstructing a complete object from its parts is a fundamental problem in many scientific domains. The purpose of this article is to provide a systematic survey on this topic. The reassembly problem requires understanding the attributes…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Jiaxin Lu , Yongqing Liang , Huijun Han , Jiacheng Hua , Junfeng Jiang , Xin Li , Qixing Huang

We present Assembler, a scalable and generalizable framework for 3D part assembly that reconstructs complete objects from input part meshes and a reference image. Unlike prior approaches that mostly rely on deterministic part pose…

Computer Vision and Pattern Recognition · Computer Science 2025-06-23 Wang Zhao , Yan-Pei Cao , Jiale Xu , Yuejiang Dong , Ying Shan

Inter-object relations underpin spatial intelligence, yet existing representations -- linguistic prepositions or object-level scene graphs -- are too coarse to specify which regions actually support, contain, or contact one another, leading…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Yinuo Bai , Peijun Xu , Kuixiang Shao , Yuyang Jiao , Jingxuan Zhang , Kaixin Yao , Jiayuan Gu , Jingyi Yu

Learning powerful deep generative models for 3D shape synthesis is largely hindered by the difficulty in ensuring plausibility encompassing correct topology and reasonable geometry. Indeed, learning the distribution of plausible 3D shapes…

Computer Vision and Pattern Recognition · Computer Science 2020-01-28 Jun Li , Chengjie Niu , Kai Xu

Cardiac function evaluation necessitates continuous, non-invasive monitoring, a capability limited in MRI. Millimeter-wave (mmWave) radar and its Synthetic Aperture Radar (SAR) mode offer a privacy-preserving and portable point-of-care…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Jinye Li , Chenxi Fu , Minghang Zheng , Yang Liu , Xiahai Zhuang , Qingchao Chen

Automated assembly of 3D fractures is essential in orthopedics, archaeology, and our daily life. This paper presents Jigsaw, a novel framework for assembling physically broken 3D objects from multiple pieces. Our approach leverages…

Computer Vision and Pattern Recognition · Computer Science 2023-10-30 Jiaxin Lu , Yifan Sun , Qixing Huang

3D image reconstruction from a limited number of 2D images has been a long-standing challenge in computer vision and image analysis. While deep learning-based approaches have achieved impressive performance in this area, existing deep…

Computer Vision and Pattern Recognition · Computer Science 2023-10-04 Nivetha Jayakumar , Tonmoy Hossain , Miaomiao Zhang
‹ Prev 1 2 3 10 Next ›