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3D shape generation aims to produce innovative 3D content adhering to specific conditions and constraints. Existing methods often decompose 3D shapes into a sequence of localized components, treating each element in isolation without…

Computer Vision and Pattern Recognition · Computer Science 2024-07-15 Ruikai Cui , Weizhe Liu , Weixuan Sun , Senbo Wang , Taizhang Shang , Yang Li , Xibin Song , Han Yan , Zhennan Wu , Shenzhou Chen , Hongdong Li , Pan Ji

In the realm of digital creativity, our potential to craft intricate 3D worlds from imagination is often hampered by the limitations of existing digital tools, which demand extensive expertise and efforts. To narrow this disparity, we…

Computer Vision and Pattern Recognition · Computer Science 2024-06-21 Longwen Zhang , Ziyu Wang , Qixuan Zhang , Qiwei Qiu , Anqi Pang , Haoran Jiang , Wei Yang , Lan Xu , Jingyi Yu

We present StdGEN++, a novel and comprehensive system for generating high-fidelity, semantically decomposed 3D characters from diverse inputs. Existing 3D generative methods often produce monolithic meshes that lack the structural…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 Yuze He , Yanning Zhou , Wang Zhao , Jingwen Ye , Zhongkai Wu , Ran Yi , Yong-Jin Liu

3D human interaction generation has emerged as a key research area, focusing on producing dynamic and contextually relevant interactions between humans and various interactive entities. Recent rapid advancements in 3D model representation…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Siyuan Fan , Wenke Huang , Xiantao Cai , Bo Du

We introduce ProcGen3D, a new approach for 3D content creation by generating procedural graph abstractions of 3D objects, which can then be decoded into rich, complex 3D assets. Inspired by the prevalent use of procedural generators in…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Xinyi Zhang , Daoyi Gao , Naiqi Li , Angela Dai

With the growing interest in deep learning algorithms and computational design in the architectural field, the need for large, accessible and diverse architectural datasets increases. We decided to tackle this problem by constructing a…

Computer Vision and Pattern Recognition · Computer Science 2021-07-08 Stanislava Fedorova , Alberto Tono , Meher Shashwat Nigam , Jiayao Zhang , Amirhossein Ahmadnia , Cecilia Bolognesi , Dominik L. Michels

Recent breakthroughs in 3D generation have enabled the synthesis of high-fidelity individual assets. However, generating 3D compositional objects from single images--particularly under occlusions--remains challenging. Existing methods often…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Hui Shan , Keyang Luo , Ming Li , Sizhe Zheng , Yanwei Fu , Zhen Chen , Xiangru Huang

Accurate 3D reconstruction of objects with reflective, transparent, or low-texture surfaces still remains notoriously challenging. Such materials often violate key assumptions in multi-view reconstruction pipelines, such as photometric…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Zhicheng Liang , Haoyi Yu , Boyan Li , Dayou Zhang , Zijian Cao , Tianyi Gong , Junhua Liu , Shuguang Cui , Fangxin Wang

Modeling and generating 3D human-object interactions from text is crucial for applications in AR, XR, and gaming. Existing approaches often rely on score distillation from text-to-image models, but their results suffer from the Janus…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Agniv Sharma , Xianghui Xie , Tom Fischer , Eddy Ilg , Gerard Pons-Moll

Recent advances in 3D generation have transitioned from multi-view 2D rendering approaches to 3D-native latent diffusion frameworks that exploit geometric priors in ground truth data. Despite progress, three key limitations persist: (1)…

Computer Vision and Pattern Recognition · Computer Science 2025-10-31 Shaocong Dong , Lihe Ding , Xiao Chen , Yaokun Li , Yuxin Wang , Yucheng Wang , Qi Wang , Jaehyeok Kim , Chenjian Gao , Zhanpeng Huang , Zibin Wang , Tianfan Xue , Dan Xu

Fast generation of high-quality 3D digital humans is important to a vast number of applications ranging from entertainment to professional concerns. Recent advances in differentiable rendering have enabled the training of 3D generative…

Computer Vision and Pattern Recognition · Computer Science 2023-07-25 Zhangyang Xiong , Di Kang , Derong Jin , Weikai Chen , Linchao Bao , Shuguang Cui , Xiaoguang Han

Creating high-fidelity 3D models of indoor environments is essential for applications in design, virtual reality, and robotics. However, manual 3D modeling remains time-consuming and labor-intensive. While recent advances in generative AI…

Computer Vision and Pattern Recognition · Computer Science 2026-01-16 Chuan Fang , Heng Li , Yixun Liang , Jia Zheng , Yongsen Mao , Yuan Liu , Rui Tang , Zihan Zhou , Ping Tan

We present DriveGen3D, a novel framework for generating high-quality and highly controllable dynamic 3D driving scenes that addresses critical limitations in existing methodologies. Current approaches to driving scene synthesis either…

The field of neural rendering has witnessed significant progress with advancements in generative models and differentiable rendering techniques. Though 2D diffusion has achieved success, a unified 3D diffusion pipeline remains unsettled.…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Yushi Lan , Fangzhou Hong , Shangchen Zhou , Shuai Yang , Xuyi Meng , Yongwei Chen , Zhaoyang Lyu , Bo Dai , Xingang Pan , Chen Change Loy

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

Detecting 3D objects keypoints is of great interest to the areas of both graphics and computer vision. There have been several 2D and 3D keypoint datasets aiming to address this problem in a data-driven way. These datasets, however, either…

Computer Vision and Pattern Recognition · Computer Science 2020-08-10 Yang You , Yujing Lou , Chengkun Li , Zhoujun Cheng , Liangwei Li , Lizhuang Ma , Weiming Wang , Cewu Lu

Answering questions about the spatial properties of the environment poses challenges for existing language and vision foundation models due to a lack of understanding of the 3D world notably in terms of relationships between objects. To…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Emilia Szymanska , Mihai Dusmanu , Jan-Willem Buurlage , Mahdi Rad , Marc Pollefeys

Creating interactive digital environments for gaming, robotics, and simulation relies on articulated 3D objects whose functionality emerges from their part geometry and kinematic structure. However, existing approaches remain fundamentally…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Penghao Wang , Siyuan Xie , Hongyu Yan , Xianghui Yang , Jingwei Huang , Chunchao Guo , Jiayuan Gu

Generative AI has made rapid progress in text, image, and video synthesis, yet text-to-3D modeling for scientific design remains particularly challenging due to limited controllability and high computational cost. Most existing 3D…

Graphics · Computer Science 2026-04-01 Rachel K. Luu , Markus J. Buehler

Recent advancements in video generation have significantly impacted daily life for both individuals and industries. However, the leading video generation models remain closed-source, resulting in a notable performance gap between industry…

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