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Related papers: PhyMix: Towards Physically Consistent Single-Image…

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We study the problem of synthesizing immersive 3D indoor scenes from one or more images. Our aim is to generate high-resolution images and videos from novel viewpoints, including viewpoints that extrapolate far beyond the input images while…

Computer Vision and Pattern Recognition · Computer Science 2022-12-02 Jing Yu Koh , Harsh Agrawal , Dhruv Batra , Richard Tucker , Austin Waters , Honglak Lee , Yinfei Yang , Jason Baldridge , Peter Anderson

We introduce PAT3D, the first physics-augmented text-to-3D scene generation framework that integrates vision-language models with physics-based simulation to produce physically plausible, simulation-ready, and intersection-free 3D scenes.…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Guying Lin , Kemeng Huang , Michael Liu , Ruihan Gao , Hanke Chen , Lyuhao Chen , Beijia Lu , Taku Komura , Yuan Liu , Jun-Yan Zhu , Minchen Li

Recent diffusion-based text-to-image customization methods have achieved significant success in understanding concrete concepts to control generation processes, such as styles and shapes. However, few efforts dive into the realistic yet…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Fan Wu , Cheng Chen , Zhoujie Fu , Jiacheng Wei , Yi Xu , Deheng Ye , Guosheng Lin

Transforming static images into interactive experiences remains a challenging task in computer vision. Tackling this challenge holds the potential to elevate mobile user experiences, notably through interactive and AR/VR applications.…

Compositional 3D scene synthesis has diverse applications across a spectrum of industries such as robotics, films, and video games, as it closely mirrors the complexity of real-world multi-object environments. Conventional works typically…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Yao Wei , Martin Renqiang Min , George Vosselman , Li Erran Li , Michael Ying Yang

Cinematic video production requires control over scene-subject composition and camera movement, but live-action shooting remains costly due to the need for constructing physical sets. To address this, we introduce the task of cinematic…

Computer Vision and Pattern Recognition · Computer Science 2026-02-09 Kaiyi Huang , Yukun Huang , Yu Li , Jianhong Bai , Xintao Wang , Zinan Lin , Xuefei Ning , Jiwen Yu , Pengfei Wan , Yu Wang , Xihui Liu

Recent advances in video generation have shown remarkable potential for constructing world simulators. However, current models still struggle to produce physically consistent results, particularly when handling large-scale or complex…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Zijun Wang , Panwen Hu , Jing Wang , Terry Jingchen Zhang , Yuhao Cheng , Long Chen , Yiqiang Yan , Zutao Jiang , Hanhui Li , Xiaodan Liang

In the field of image processing, applying intricate semantic modifications within existing images remains an enduring challenge. This paper introduces a pioneering framework that integrates viewpoint information to enhance the control of…

Computer Vision and Pattern Recognition · Computer Science 2024-05-09 Jinbin Bai , Zhen Dong , Aosong Feng , Xiao Zhang , Tian Ye , Kaicheng Zhou

4D content generation aims to create dynamically evolving 3D content that responds to specific input objects such as images or 3D representations. Current approaches typically incorporate physical priors to animate 3D representations, but…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 Jiajing Lin , Zhenzhong Wang , Dejun Xu , Shu Jiang , YunPeng Gong , Min Jiang

We introduce 3inGAN, an unconditional 3D generative model trained from 2D images of a single self-similar 3D scene. Such a model can be used to produce 3D "remixes" of a given scene, by mapping spatial latent codes into a 3D volumetric…

Computer Vision and Pattern Recognition · Computer Science 2022-11-29 Animesh Karnewar , Oliver Wang , Tobias Ritschel , Niloy Mitra

Image generation models trained on large datasets can synthesize high-quality images but often produce spatially inconsistent and distorted images due to limited information about the underlying structures and spatial layouts. In this work,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-27 Hyundo Lee , Suhyung Choi , Inwoo Hwang , Byoung-Tak Zhang

Despite substantial progress in text-driven 3D human motion synthesis, generating realistic multi-person interaction sequences remains challenging. Notably, body inter-penetration is a pervasive issue from both data acquisition to the…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Nan Lei , Yuan-Ming Li , Ling-An Zeng , Liang Xu , Zhi-Wei Xia , Hui-Wen Huang , Fa-Ting Hong , Wei-Shi Zheng

Physical principles are fundamental to realistic visual simulation, but remain a significant oversight in transformer-based video generation. This gap highlights a critical limitation in rendering rigid body motion, a core tenet of…

Computer Vision and Pattern Recognition · Computer Science 2026-01-19 Qiyuan Zhang , Biao Gong , Shuai Tan , Zheng Zhang , Yujun Shen , Xing Zhu , Yuyuan Li , Kelu Yao , Chunhua Shen , Changqing Zou

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

3D animation is central to modern visual media, yet traditional production pipelines remain labor-intensive, expertise-demanding, and computationally expensive. Recent AIGC-based approaches partially automate asset creation and rigging, but…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Yupeng Zhu , Xiongzhen Zhang , Ye Chen , Bingbing Ni

Text-to-video generative models have made significant strides in recent years, producing high-quality videos that excel in both aesthetic appeal and accurate instruction following, and have become central to digital art creation and user…

Machine Learning · Computer Science 2025-05-02 Xuyang Guo , Jiayan Huo , Zhenmei Shi , Zhao Song , Jiahao Zhang , Jiale Zhao

We are witnessing significant breakthroughs in the technology for generating 3D objects from text. Existing approaches either leverage large text-to-image models to optimize a 3D representation or train 3D generators on object-centric…

Computer Vision and Pattern Recognition · Computer Science 2023-12-15 Qihang Zhang , Chaoyang Wang , Aliaksandr Siarohin , Peiye Zhuang , Yinghao Xu , Ceyuan Yang , Dahua Lin , Bolei Zhou , Sergey Tulyakov , Hsin-Ying Lee

Video generative models have made remarkable progress, yet they often yield visual artifacts that violate grounding in physical dynamics. Recent works such as PhysGen3D tackle single image-to-3D physics through mesh reconstruction and…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Hwidong Kim , Yunho Kim , Tae-Kyun Kim

Data center (DC) infrastructure serves as the backbone to support the escalating demand for computing capacity. Traditional design methodologies that blend human expertise with specialized simulation tools scale poorly with the increasing…

Artificial Intelligence · Computer Science 2025-12-16 Minghao LI , Ruihang Wang , Rui Tan , Yonggang Wen

Joint audio-video generation models are rapidly approaching professional production quality, raising a central question: do they understand audio-visual physics, or merely generate plausible sounds and frames that violate real-world…