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Recent years have witnessed a surge in the development of protein structural tokenization methods, which chunk protein 3D structures into discrete or continuous representations. Structure tokenization enables the direct application of…

Quantitative Methods · Quantitative Biology 2025-06-26 Xinyu Yuan , Zichen Wang , Marcus Collins , Huzefa Rangwala

Detecting 3D keypoints from point clouds is important for shape reconstruction, while this work investigates the dual question: can shape reconstruction benefit 3D keypoint detection? Existing methods either seek salient features according…

Computer Vision and Pattern Recognition · Computer Science 2022-10-18 Chengliang Zhong , Peixing You , Xiaoxue Chen , Hao Zhao , Fuchun Sun , Guyue Zhou , Xiaodong Mu , Chuang Gan , Wenbing Huang

A learning-based 3D reconstruction method for long-span bridges is proposed in this paper. 3D reconstruction generates a 3D computer model of a real object or scene from images, it involves many stages and open problems. Existing…

Computer Vision and Pattern Recognition · Computer Science 2020-05-22 Fangqiao Hu , Jin Zhao , Yong Huang , Hui Li

Despite rapid advancements in the capabilities of generative models, pretrained text-to-image models still struggle in capturing the semantics conveyed by complex prompts that compound multiple objects and instance-level attributes.…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Etai Sella , Yanir Kleiman , Hadar Averbuch-Elor

In materials science, the challenge of rapid prototyping materials with desired properties often involves extensive experimentation to find suitable microstructures. Additionally, finding microstructures for given properties is typically an…

Machine Learning · Computer Science 2024-05-22 Sébastien Bompas , Stefan Sandfeld

Inspired by cognitive theories, we introduce AnyHome, a framework that translates any text into well-structured and textured indoor scenes at a house-scale. By prompting Large Language Models (LLMs) with designed templates, our approach…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Rao Fu , Zehao Wen , Zichen Liu , Srinath Sridhar

Generating 3D scenes from human motion sequences supports numerous applications, including virtual reality and architectural design. However, previous auto-regression-based human-aware 3D scene generation methods have struggled to…

Computer Vision and Pattern Recognition · Computer Science 2024-08-21 Xiaolin Hong , Hongwei Yi , Fazhi He , Qiong Cao

The ability to generate novel, diverse, and realistic 3D shapes along with associated part semantics and structure is central to many applications requiring high-quality 3D assets or large volumes of realistic training data. A key challenge…

Graphics · Computer Science 2019-08-05 Kaichun Mo , Paul Guerrero , Li Yi , Hao Su , Peter Wonka , Niloy Mitra , Leonidas J. Guibas

Generating realistic 3D indoor scenes from user inputs remains a challenging problem in computer vision and graphics, requiring careful balance of geometric consistency, spatial relationships, and visual realism. While neural generation…

Computer Vision and Pattern Recognition · Computer Science 2025-06-30 Mengqi Zhou , Xipeng Wang , Yuxi Wang , Zhaoxiang Zhang

With the growing demand for high-fidelity 3D models from 2D images, existing methods still face significant challenges in accurately reproducing fine-grained geometric details due to limitations in domain gaps and inherent ambiguities in…

Graphics · Computer Science 2025-04-01 Chongjie Ye , Yushuang Wu , Ziteng Lu , Jiahao Chang , Xiaoyang Guo , Jiaqing Zhou , Hao Zhao , Xiaoguang Han

Simulation-ready physical 3D assets have emerged as a promising direction owing to their broad applicability in downstream tasks. However, most existing 3D generation methods either neglect physical properties or are limited to a single…

Computer Vision and Pattern Recognition · Computer Science 2026-05-22 Ziang Cao , Yinghao Liu , Haitian Li , Runmao Yao , Fangzhou Hong , Zhaoxi Chen , Liang Pan , Ziwei Liu

Interactive 3D simulated objects are crucial in AR/VR, animations, and robotics, driving immersive experiences and advanced automation. However, creating these articulated objects requires extensive human effort and expertise, limiting…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Long Le , Jason Xie , William Liang , Hung-Ju Wang , Yue Yang , Yecheng Jason Ma , Kyle Vedder , Arjun Krishna , Dinesh Jayaraman , Eric Eaton

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

Image-to-3D models increasingly rely on hierarchical generation to disentangle geometry and texture. However, the design choices underlying these two-stage models--particularly the optimal choice of intermediate geometric…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Rishabh Kabra , Drew A. Hudson , Sjoerd van Steenkiste , Joao Carreira , Niloy J. Mitra

Recent multimodal large language models have achieved strong performance in unified text and image understanding and generation, yet extending such native capability to 3D remains challenging due to limited data. Compared to abundant 2D…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Chongjie Ye , Cheng Cao , Chuanyu Pan , Yiming Hao , Yihao Zhi , Yuanming Hu , Xiaoguang Han

Many real-world prediction tasks, particularly those involving entities such as customers or patients, involve both {sequential} and {relational} data. Each entity maintains its own sequence of events while simultaneously engaging in…

Machine Learning · Computer Science 2026-04-03 Yuen Chen , Yulun Wu , Samuel Sharpe , Igor Melnyk , Nam H. Nguyen , Furong Huang , C. Bayan Bruss , Rizal Fathony

3D shape modeling is labor-intensive, time-consuming, and requires years of expertise. To facilitate 3D shape modeling, we propose a 3D shape generation network that takes a 3D VR sketch as a condition. We assume that sketches are created…

Computer Vision and Pattern Recognition · Computer Science 2024-01-11 Ling Luo , Pinaki Nath Chowdhury , Tao Xiang , Yi-Zhe Song , Yulia Gryaditskaya

This paper investigates the generative designing of a bracket that aids in the rotation of a linkage mounted on it with a revolute joint. Generative design is a term that is generally used when we care about weight reduction and performance…

Applied Physics · Physics 2021-01-13 Bashu Aman

Existing generative models for 3D shapes can synthesize high-fidelity and visually plausible shapes. For certain classes of shapes that have undergone an engineering design process, the realism of the shape is tightly coupled with the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Yingxuan You , Chen Zhao , Hantao Zhang , Ming Xu , Pascal Fua

Learning to generate textures for a novel 3D mesh given a collection of 3D meshes and real-world 2D images is an important problem with applications in various domains such as 3D simulation, augmented and virtual reality, gaming,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-08 Dharma KC , Clayton T. Morrison