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We present a learning framework for abstracting complex shapes by learning to assemble objects using 3D volumetric primitives. In addition to generating simple and geometrically interpretable explanations of 3D objects, our framework also…

Computer Vision and Pattern Recognition · Computer Science 2018-08-06 Shubham Tulsiani , Hao Su , Leonidas J. Guibas , Alexei A. Efros , Jitendra Malik

The success of various applications including robotics, digital content creation, and visualization demand a structured and abstract representation of the 3D world from limited sensor data. Inspired by the nature of human perception of 3D…

Computer Vision and Pattern Recognition · Computer Science 2017-08-08 Chuhang Zou , Ersin Yumer , Jimei Yang , Duygu Ceylan , Derek Hoiem

3D shape generation is a challenging problem due to the high-dimensional output space and complex part configurations of real-world objects. As a result, existing algorithms experience difficulties in accurate generative modeling of 3D…

Computer Vision and Pattern Recognition · Computer Science 2019-06-11 Salman H. Khan , Yulan Guo , Munawar Hayat , Nick Barnes

3D Shape representation has substantial effects on 3D shape reconstruction. Primitive-based representations approximate a 3D shape mainly by a set of simple implicit primitives, but the low geometrical complexity of the primitives limits…

Computer Vision and Pattern Recognition · Computer Science 2021-08-20 Mohsen Yavartanoo , JaeYoung Chung , Reyhaneh Neshatavar , Kyoung Mu Lee

The abstraction of 3D objects with simple geometric primitives like cuboids allows to infer structural information from complex geometry. It is important for 3D shape understanding, structural analysis and geometric modeling. We introduce a…

Computer Vision and Pattern Recognition · Computer Science 2025-02-05 Gregor Kobsik , Morten Henkel , Yanjiang He , Victor Czech , Tim Elsner , Isaak Lim , Leif Kobbelt

Sequential assembly with geometric primitives has drawn attention in robotics and 3D vision since it yields a practical blueprint to construct a target shape. However, due to its combinatorial property, a greedy method falls short of…

Computer Vision and Pattern Recognition · Computer Science 2020-11-26 Jungtaek Kim , Hyunsoo Chung , Jinhwi Lee , Minsu Cho , Jaesik Park

Impressive progress in 3D shape extraction led to representations that can capture object geometries with high fidelity. In parallel, primitive-based methods seek to represent objects as semantically consistent part arrangements. However,…

Computer Vision and Pattern Recognition · Computer Science 2021-03-19 Despoina Paschalidou , Angelos Katharopoulos , Andreas Geiger , Sanja Fidler

Accurate 3D shape abstraction from a single 2D image is a long-standing problem in computer vision and graphics. By leveraging a set of primitives to represent the target shape, recent methods have achieved promising results. However, these…

Computer Vision and Pattern Recognition · Computer Science 2023-10-05 Di Liu , Xiang Yu , Meng Ye , Qilong Zhangli , Zhuowei Li , Zhixing Zhang , Dimitris N. Metaxas

Reconstructing 3D object from a single image (RGB or depth) is a fundamental problem in visual scene understanding and yet remains challenging due to its ill-posed nature and complexity in real-world scenes. To address those challenges, we…

Computer Vision and Pattern Recognition · Computer Science 2021-09-10 Qian He , Desen Zhou , Bo Wan , Xuming He

Retrieving the 3D kinematics of articulated objects from monocular video is a fundamental challenge in computer vision. Existing methods rely on complex video setups or cues such as long-term point tracking or wide-baseline matching, but…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Arslan Artykov , Tom Ravaud , Nicolás Violante-Grezzi , Vincent Lepetit

Humans show high-level of abstraction capabilities in games that require quickly communicating object information. They decompose the message content into multiple parts and communicate them in an interpretable protocol. Toward equipping…

Computer Vision and Pattern Recognition · Computer Science 2022-07-28 Stephan Alaniz , Massimiliano Mancini , Anjan Dutta , Diego Marcos , Zeynep Akata

The task of shape abstraction with semantic part consistency is challenging due to the complex geometries of natural objects. Recent methods learn to represent an object shape using a set of simple primitives to fit the target.…

Computer Vision and Pattern Recognition · Computer Science 2023-09-06 Di Liu , Long Zhao , Qilong Zhangli , Yunhe Gao , Ting Liu , Dimitris N. Metaxas

3D shape abstraction has drawn great interest over the years. Apart from low-level representations such as meshes and voxels, researchers also seek to semantically abstract complex objects with basic geometric primitives. Recent deep…

Computer Vision and Pattern Recognition · Computer Science 2022-07-20 Yuwei Wu , Weixiao Liu , Sipu Ruan , Gregory S. Chirikjian

Representing a 3D shape with a set of primitives can aid perception of structure, improve robotic object manipulation, and enable editing, stylization, and compression of 3D shapes. Existing methods either use simple parametric primitives…

Computer Vision and Pattern Recognition · Computer Science 2023-03-06 Xianghao Xu , Paul Guerrero , Matthew Fisher , Siddhartha Chaudhuri , Daniel Ritchie

Recent advancements in AI-driven 3D model generation have leveraged cross modality, yet generating models with smooth surfaces and minimizing storage overhead remain challenges. This paper introduces a novel multi-stage framework for…

Graphics · Computer Science 2025-10-13 Yiming Liang , Huan Yu , Zili Wang , Shuyou Zhang , Guodong Yi , Jin Wang , Jianrong Tan

Recently, 3D assets created via reconstruction and generation have matched the quality of manually crafted assets, highlighting their potential for replacement. However, this potential is largely unrealized because these assets always need…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Yiwen Chen , Tong He , Di Huang , Weicai Ye , Sijin Chen , Jiaxiang Tang , Xin Chen , Zhongang Cai , Lei Yang , Gang Yu , Guosheng Lin , Chi Zhang

Advances in 3D-aware generative models have pushed the boundary of image synthesis with explicit camera control. To achieve high-resolution image synthesis, several attempts have been made to design efficient generators, such as hybrid…

Computer Vision and Pattern Recognition · Computer Science 2023-04-03 Mallikarjun B R , Xingang Pan , Mohamed Elgharib , Christian Theobalt

Aggregating base elements into rigid objects such as furniture or sculptures is a great way for designers to convey a specific look and feel. Unfortunately, there is no existing solution to help model structurally sound aggregates. The…

Graphics · Computer Science 2018-11-08 Jérémie Dumas , Jonàs Martínez , Sylvain Lefebvre , Li-Yi Wei

Structured shape completion recovers missing geometry as primitives rather than as unstructured points, which enables primitive-based surface reconstruction. Instead of following the prevailing cascade, we rethink how primitives and points…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Zhaiyu Chen , Yuqing Wang , Xiao Xiang Zhu

We present a dynamic reconstruction system that receives a casual monocular RGB video as input, and outputs a complete and persistent reconstruction of the scene. In other words, we reconstruct not only the the currently visible parts of…

Computer Vision and Pattern Recognition · Computer Science 2025-12-19 Kirill Mazur , Marwan Taher , Andrew J. Davison
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