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200 papers

Autoregressive models for 3D mesh generation suffer from a fundamental limitation: they flatten meshes into long vertex-coordinate sequences. This results in prohibitive computational costs, hindering the efficient synthesis of…

Computer Vision and Pattern Recognition · Computer Science 2026-03-04 Hanxiao Wang , Yuan-Chen Guo , Ying-Tian Liu , Zi-Xin Zou , Biao Zhang , Weize Quan , Ding Liang , Yan-Pei Cao , Dong-Ming Yan

Polygon meshes are an efficient representation of 3D geometry, and are of central importance in computer graphics, robotics and games development. Existing learning-based approaches have avoided the challenges of working with 3D meshes,…

Graphics · Computer Science 2020-02-26 Charlie Nash , Yaroslav Ganin , S. M. Ali Eslami , Peter W. Battaglia

Drug development is a critical but notoriously resource- and time-consuming process. In this manuscript, we develop a novel generative artificial intelligence (genAI) method DiffSMol to facilitate drug development. DiffSmol generates 3D…

Machine Learning · Computer Science 2025-02-11 Ziqi Chen , Bo Peng , Tianhua Zhai , Daniel Adu-Ampratwum , Xia Ning

The dominant paradigm for high-fidelity 3D generation relies on a VAE-Diffusion pipeline, where the VAE's reconstruction capability sets a firm upper bound on generation quality. A fundamental challenge limiting existing VAEs is the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Guan Luo , Xiu Li , Rui Chen , Xuanyu Yi , Jing Lin , Chia-Hao Chen , Jiahang Liu , Song-Hai Zhang , Jianfeng Zhang

The generation of 3D clothed humans has attracted increasing attention in recent years. However, existing work cannot generate layered high-quality 3D humans with consistent body structures. As a result, these methods are unable to…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Yi Wang , Jian Ma , Ruizhi Shao , Qiao Feng , Yu-Kun Lai , Yebin Liu , Kun Li

The ability to map descriptions of scenes to 3D geometric representations has many applications in areas such as art, education, and robotics. However, prior work on the text to 3D scene generation task has used manually specified object…

Computation and Language · Computer Science 2015-06-08 Angel Chang , Will Monroe , Manolis Savva , Christopher Potts , Christopher D. Manning

We present Meta 3D AssetGen (AssetGen), a significant advancement in text-to-3D generation which produces faithful, high-quality meshes with texture and material control. Compared to works that bake shading in the 3D object's appearance,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-03 Yawar Siddiqui , Tom Monnier , Filippos Kokkinos , Mahendra Kariya , Yanir Kleiman , Emilien Garreau , Oran Gafni , Natalia Neverova , Andrea Vedaldi , Roman Shapovalov , David Novotny

Structure-based drug design involves finding ligand molecules that exhibit structural and chemical complementarity to protein pockets. Deep generative methods have shown promise in proposing novel molecules from scratch (de-novo design),…

Quantitative Methods · Quantitative Biology 2021-11-09 Pavol Drotár , Arian Rokkum Jamasb , Ben Day , Cătălina Cangea , Pietro Liò

Generating 3D visual scenes is at the forefront of visual generative AI, but current 3D generation techniques struggle with generating scenes with multiple high-resolution objects. Here we introduce Lay-A-Scene, which solves the task of…

Computer Vision and Pattern Recognition · Computer Science 2024-06-05 Ohad Rahamim , Hilit Segev , Idan Achituve , Yuval Atzmon , Yoni Kasten , Gal Chechik

The generation and completion of 3D objects represent a transformative challenge in computer vision. Generative Adversarial Networks (GANs) have recently demonstrated strong potential in synthesizing realistic visual data. However, they…

Computer Vision and Pattern Recognition · Computer Science 2026-02-10 Yahia Hamdi , Nicolas Andrialovanirina , Kélig Mahé , Emilie Poisson Caillault

Accurate and efficient 3D medical image segmentation is essential for clinical AI, where models must remain reliable under stringent memory, latency, and data availability constraints. Transformer-based methods achieve strong accuracy but…

Machine Learning · Computer Science 2026-03-10 Kavyansh Tyagi , Vishwas Rathi , Puneet Goyal

Deep generative architectures provide a way to model not only images but also complex, 3-dimensional objects, such as point clouds. In this work, we present a novel method to obtain meaningful representations of 3D shapes that can be used…

Machine Learning · Computer Science 2019-05-03 Maciej Zamorski , Maciej Zięba , Piotr Klukowski , Rafał Nowak , Karol Kurach , Wojciech Stokowiec , Tomasz Trzciński

High-fidelity surgical video generation can greatly improve medical training and the development of AI, adapting these generative models for precise video editing remains a formidable challenge. Modifying surgical attributes, such as…

Computer Vision and Pattern Recognition · Computer Science 2026-05-11 Ritul Jangir , Arkya Jyoti Bagchi , Aiman Farooq , Mangalton Okram , Saurabh Seetaram Korgaonkar , Deepak Mishra

We consider the problem of scaling deep generative shape models to high-resolution. Drawing motivation from the canonical view representation of objects, we introduce a novel method for the fast up-sampling of 3D objects in voxel space…

Computer Vision and Pattern Recognition · Computer Science 2018-11-16 Edward Smith , Scott Fujimoto , David Meger

Recent advances in generative AI have brought incredible breakthroughs in several areas, including medical imaging. These generative models have tremendous potential not only to help safely share medical data via synthetic datasets but also…

Generative models for 3D object synthesis have seen significant advancements with the incorporation of prior knowledge distilled from 2D diffusion models. Nevertheless, challenges persist in the form of multi-view geometric inconsistencies…

Computer Vision and Pattern Recognition · Computer Science 2023-11-20 Lincong Feng , Muyu Wang , Maoyu Wang , Kuo Xu , Xiaoli Liu

Recent advancements in generative models have enabled the creation of dynamic 4D content - 3D objects in motion - based on text prompts, which holds potential for applications in virtual worlds, media, and gaming. Existing methods provide…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Ohad Rahamim , Ori Malca , Dvir Samuel , Gal Chechik

3D fragment reassembly aims to recover the rigid poses of unordered fragment point clouds or meshes in a common object coordinate system to reconstruct the complete shape. The problem becomes particularly challenging as the number of…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Hanze Jia , Chunshi Wang , Yuxiao Yang , Zhonghua Jiang , Yawei Luo , Shuainan Ye , Tan Tang

3D shape creation and modeling remains a challenging task especially for novice users. Many methods in the field of computer graphics have been proposed to automate the often repetitive and precise operations needed during the modeling of…

Graphics · Computer Science 2015-06-24 Ibraheem Alhashim

Autonomous robots that interact with their environment require a detailed semantic scene model. For this, volumetric semantic maps are frequently used. The scene understanding can further be improved by including object-level information in…

Computer Vision and Pattern Recognition · Computer Science 2022-11-22 Julian Hau , Simon Bultmann , Sven Behnke