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Related papers: Text-To-4D Dynamic Scene Generation

200 papers

This paper addresses the challenge of learning semantically and functionally meaningful 3D motion priors from real-world videos, in order to enable prediction of future 3D scene motion from a single input image. We propose a novel…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Jiahui Lei , Kyle Genova , George Kopanas , Noah Snavely , Leonidas Guibas

Recent text-to-scene generation approaches largely reduced the manual efforts required to create 3D scenes. However, their focus is either to generate a scene layout or to generate objects, and few generate both. The generated scene layout…

Computer Vision and Pattern Recognition · Computer Science 2026-04-30 Zhenggang Tang , Yuehao Wang , Yuchen Fan , Jun-Kun Chen , Yu-Ying Yeh , Kihyuk Sohn , Zhangyang Wang , Qixing Huang , Alexander Schwing , Rakesh Ranjan , Dilin Wang , Zhicheng Yan

We present a scene representation, which we call a tactile-augmented radiance field (TaRF), that brings vision and touch into a shared 3D space. This representation can be used to estimate the visual and tactile signals for a given 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-05-08 Yiming Dou , Fengyu Yang , Yi Liu , Antonio Loquercio , Andrew Owens

Neural Radiance Fields (NeRFs) have shown great potential in modeling 3D scenes. Dynamic NeRFs extend this model by capturing time-varying elements, typically using deformation fields. The existing dynamic NeRFs employ a similar Eulerian…

Computer Vision and Pattern Recognition · Computer Science 2025-02-13 Ancheng Lin , Yusheng Xiang , Jun Li , Mukesh Prasad

Neural Radiance Fields (NeRFs) excel in photorealistically rendering static scenes. However, rendering dynamic, long-duration radiance fields on ubiquitous devices remains challenging, due to data storage and computational constraints. In…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Liao Wang , Kaixin Yao , Chengcheng Guo , Zhirui Zhang , Qiang Hu , Jingyi Yu , Lan Xu , Minye Wu

We present a method that achieves state-of-the-art results for synthesizing novel views of complex scenes by optimizing an underlying continuous volumetric scene function using a sparse set of input views. Our algorithm represents a scene…

Computer Vision and Pattern Recognition · Computer Science 2020-08-05 Ben Mildenhall , Pratul P. Srinivasan , Matthew Tancik , Jonathan T. Barron , Ravi Ramamoorthi , Ren Ng

The synthesis of immersive 3D scenes from text is rapidly maturing, driven by novel video generative models and feed-forward 3D reconstruction, with vast potential in AR/VR and world modeling. While panoramic images have proven effective…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Felix Wimbauer , Fabian Manhardt , Michael Oechsle , Nikolai Kalischek , Christian Rupprecht , Daniel Cremers , Federico Tombari

This paper aims to tackle the challenge of efficiently producing interactive free-viewpoint videos. Some recent works equip neural radiance fields with image encoders, enabling them to generalize across scenes. When processing dynamic…

Computer Vision and Pattern Recognition · Computer Science 2022-11-29 Haotong Lin , Sida Peng , Zhen Xu , Yunzhi Yan , Qing Shuai , Hujun Bao , Xiaowei Zhou

Novel view synthesis (NVS) is a challenging task in computer vision that involves synthesizing new views of a scene from a limited set of input images. Neural Radiance Fields (NeRF) have emerged as a powerful approach to address this…

Computer Vision and Pattern Recognition · Computer Science 2023-03-16 Shuja Khalid , Frank Rudzicz

Generating 3D human motions from text is a challenging yet valuable task. The key aspects of this task are ensuring text-motion consistency and achieving generation diversity. Although recent advancements have enabled the generation of…

Computer Vision and Pattern Recognition · Computer Science 2025-08-29 Zheng Qin , Yabing Wang , Minghui Yang , Sanping Zhou , Ming Yang , Le Wang

Recent advances in text-to-3D scene generation have demonstrated significant potential to transform content creation across multiple industries. Although the research community has made impressive progress in addressing the challenges of…

Designing complex 3D scenes has been a tedious, manual process requiring domain expertise. Emerging text-to-3D generative models show great promise for making this task more intuitive, but existing approaches are limited to object-level…

Computer Vision and Pattern Recognition · Computer Science 2023-03-24 Ryan Po , Gordon Wetzstein

Generating human motions from textual descriptions has gained growing research interest due to its wide range of applications. However, only a few works consider human-scene interactions together with text conditions, which is crucial for…

Computer Vision and Pattern Recognition · Computer Science 2024-05-14 Zhi Cen , Huaijin Pi , Sida Peng , Zehong Shen , Minghui Yang , Shuai Zhu , Hujun Bao , Xiaowei Zhou

Recent techniques for text-to-4D generation synthesize dynamic 3D scenes using supervision from pre-trained text-to-video models. However, existing representations for motion, such as deformation models or time-dependent neural…

Computer Vision and Pattern Recognition · Computer Science 2024-10-16 Sherwin Bahmani , Xian Liu , Wang Yifan , Ivan Skorokhodov , Victor Rong , Ziwei Liu , Xihui Liu , Jeong Joon Park , Sergey Tulyakov , Gordon Wetzstein , Andrea Tagliasacchi , David B. Lindell

Novel view synthesis (NVS) has shown significant promise for applications in cinematographic production, particularly through the exploitation of Neural Radiance Fields (NeRF) and Gaussian Splatting (GS). These methods model real 3D scenes,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Adrian Azzarelli , Nantheera Anantrasirichai , David R Bull

Extensions of Neural Radiance Fields (NeRFs) to model dynamic scenes have enabled their near photo-realistic, free-viewpoint rendering. Although these methods have shown some potential in creating immersive experiences, two drawbacks limit…

Computer Vision and Pattern Recognition · Computer Science 2024-06-07 Xinhang Liu , Yu-Wing Tai , Chi-Keung Tang , Pedro Miraldo , Suhas Lohit , Moitreya Chatterjee

This paper proposes a neural radiance field (NeRF) approach for novel view synthesis of dynamic scenes using forward warping. Existing methods often adopt a static NeRF to represent the canonical space, and render dynamic images at other…

Computer Vision and Pattern Recognition · Computer Science 2023-10-02 Xiang Guo , Jiadai Sun , Yuchao Dai , Guanying Chen , Xiaoqing Ye , Xiao Tan , Errui Ding , Yumeng Zhang , Jingdong Wang

Creating high-quality and interactive virtual environments, such as games and simulators, often involves complex and costly manual modeling processes. In this paper, we present Video2Game, a novel approach that automatically converts videos…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Hongchi Xia , Zhi-Hao Lin , Wei-Chiu Ma , Shenlong Wang

As recent advances in Neural Radiance Fields (NeRF) have enabled high-fidelity 3D face reconstruction and novel view synthesis, its manipulation also became an essential task in 3D vision. However, existing manipulation methods require…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Sungwon Hwang , Junha Hyung , Daejin Kim , Min-Jung Kim , Jaegul Choo

Neural radiance fields (NeRF) has gained significant attention for its exceptional visual effects. However, most existing NeRF methods reconstruct 3D scenes from RGB images captured by visible light cameras. In practical scenarios like…

Computer Vision and Pattern Recognition · Computer Science 2024-10-08 Chonghao Zhong , Chao Xu
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