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Related papers: Phys4DGen: Physics-Compliant 4D Generation with Mu…

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Recent advancements in 4D generation have demonstrated its remarkable capability in synthesizing photorealistic renderings of dynamic 3D scenes. However, despite achieving impressive visual performance, almost all existing methods overlook…

Sound · Computer Science 2026-03-02 Siyi Xie , Hanxin Zhu , Xinyi Chen , Tianyu He , Xin Li , Zhibo Chen

3D Gaussian Splatting (3DGS) has garnered significant attention due to its superior scene representation fidelity and real-time rendering performance, especially for dynamic 3D scene reconstruction (\textit{i.e.}, 4D reconstruction).…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Henan Wang , Hanxin Zhu , Xinliang Gong , Tianyu He , Xin Li , Zhibo Chen

We present a deep generative scene modeling technique for indoor environments. Our goal is to train a generative model using a feed-forward neural network that maps a prior distribution (e.g., a normal distribution) to the distribution of…

Computer Vision and Pattern Recognition · Computer Science 2018-08-08 Zaiwei Zhang , Zhenpei Yang , Chongyang Ma , Linjie Luo , Alexander Huth , Etienne Vouga , Qixing Huang

Generating articulated assets is crucial for robotics, digital twins, and embodied intelligence. Existing generative models often rely on single-view inputs representing closed states, resulting in ambiguous or unrealistic kinematic…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Haowen Wang , Xiaoping Yuan , Fugang Zhang , Rui Jian , Yuanwei Zhu , Xiuquan Qiao , Yakun Huang

Automatic 3D content creation has gained increasing attention recently, due to its potential in various applications such as video games, film industry, and AR/VR. Recent advancements in diffusion models and multimodal models have notably…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Yitong Wang , Xudong Xu , Li Ma , Haoran Wang , Bo Dai

Recent advances in Gaussian Splatting have enabled fast, high-fidelity 3D scene generation, yet these methods remain purely visual and lack an understanding of how shapes behave in the physical world. We introduce Physics-Guided 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Zachary Lee , Maxwell Jacobson , Yexiang Xue

Given a 3D mesh, we aim to synthesize 3D textures that correspond to arbitrary textual descriptions. Current methods for generating and assembling textures from sampled views often result in prominent seams or excessive smoothing. To tackle…

Computer Vision and Pattern Recognition · Computer Science 2024-08-05 Dong Huo , Zixin Guo , Xinxin Zuo , Zhihao Shi , Juwei Lu , Peng Dai , Songcen Xu , Li Cheng , Yee-Hong Yang

Recent advances in diffusion-based video generation have achieved remarkable visual realism but still struggle to obey basic physical laws such as gravity, inertia, and collision. Generated objects often move inconsistently across frames,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Lin Geng Foo , Mark He Huang , Alexandros Lattas , Stylianos Moschoglou , Thabo Beeler , Christian Theobalt

World Generation Models are emerging as a cornerstone of next-generation multimodal intelligence systems. Unlike traditional 2D visual generation, World Models aim to construct realistic, dynamic, and physically consistent 3D/4D worlds from…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Yiting Lu , Wei Luo , Peiyan Tu , Haoran Li , Hanxin Zhu , Zihao Yu , Xingrui Wang , Xinyi Chen , Xinge Peng , Xin Li , Zhibo Chen

Generating 3D models lies at the core of computer graphics and has been the focus of decades of research. With the emergence of advanced neural representations and generative models, the field of 3D content generation is developing rapidly,…

Computer Vision and Pattern Recognition · Computer Science 2024-02-01 Xiaoyu Li , Qi Zhang , Di Kang , Weihao Cheng , Yiming Gao , Jingbo Zhang , Zhihao Liang , Jing Liao , Yan-Pei Cao , Ying Shan

Generating 4D scenes from a single-view video is inherently ill-posed: a single viewpoint lacks the information needed to recover a complete, dynamic scene with full coverage. Existing methods are typically limited to monocular videos,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Tingxi Chen , Ke Hao , Yabo Chen , Zhengxue Cheng , Rong Xie , Li Song , Haibin Huang , Chi Zhang , Xuelong Li

This paper presents a novel decoder-based approach for generating manufacturable 3D structures optimized for additive manufacturing. We introduce a deep learning framework that decodes latent representations into geometrically valid,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-14 Abhishek Kumar

3D content creation has achieved significant progress in terms of both quality and speed. Although current feed-forward models can produce 3D objects in seconds, their resolution is constrained by the intensive computation required during…

Computer Vision and Pattern Recognition · Computer Science 2024-02-08 Jiaxiang Tang , Zhaoxi Chen , Xiaokang Chen , Tengfei Wang , Gang Zeng , Ziwei Liu

Methods that use neural networks for synthesizing 3D shapes in the form of a part-based representation have been introduced over the last few years. These methods represent shapes as a graph or hierarchy of parts and enable a variety of…

Graphics · Computer Science 2024-09-20 Yanran Guan , Oliver van Kaick

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

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

Most earlier 3D structure-based molecular generation approaches follow an atom-wise paradigm, incrementally adding atoms to a partially built molecular fragment within protein pockets. These methods, while effective in designing tightly…

We introduce Follow-Your-Creation, a novel 4D video creation framework capable of both generating and editing 4D content from a single monocular video input. By leveraging a powerful video inpainting foundation model as a generative prior,…

Computer Vision and Pattern Recognition · Computer Science 2025-06-06 Yue Ma , Kunyu Feng , Xinhua Zhang , Hongyu Liu , David Junhao Zhang , Jinbo Xing , Yinhan Zhang , Ayden Yang , Zeyu Wang , Qifeng Chen

Recent breakthroughs in text-guided image generation have significantly advanced the field of 3D generation. While generating a single high-quality 3D object is now feasible, generating multiple objects with reasonable interactions within a…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Chongjian Ge , Chenfeng Xu , Yuanfeng Ji , Chensheng Peng , Masayoshi Tomizuka , Ping Luo , Mingyu Ding , Varun Jampani , Wei Zhan

In recent years, the demand for 3D content has grown exponentially with the intelligent upgrade of interactive media, extended reality (XR), and Metaverse industries. In order to overcome the limitations of traditional manual modeling…

Graphics · Computer Science 2025-12-23 Xiang Tang , Ruotong Li , Xiaopeng Fan