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Video generation is experiencing rapid growth, driven by advances in diffusion models and the development of better and larger datasets. However, producing high-quality videos remains challenging due to the high-dimensional data and the…

Computer Vision and Pattern Recognition · Computer Science 2025-04-10 Elia Peruzzo , Dejia Xu , Xingqian Xu , Humphrey Shi , Nicu Sebe

4D generation, or dynamic 3D content generation, integrates spatial, temporal, and view dimensions to model realistic dynamic scenes, playing a foundational role in advancing world models and physical AI. However, maintaining long-chain…

Graphics · Computer Science 2026-04-01 Yuanbin Man , Ying Huang , Zhile Ren , Miao Yin

Recent video diffusion models have achieved impressive capabilities as large-scale generative world models. However, these models often struggle with fine-grained physical consistency, exhibiting physically implausible dynamics over time.…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Haoran Lu , Shang Wu , Jianshu Zhang , Maojiang Su , Guo Ye , Chenwei Xu , Lie Lu , Pranav Maneriker , Fan Du , Manling Li , Zhaoran Wang , Han Liu

The rising popularity of immersive visual experiences has increased interest in stereoscopic 3D video generation. Despite significant advances in video synthesis, creating 3D videos remains challenging due to the relative scarcity of 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-05-02 Michal Geyer , Omer Tov , Linyi Jin , Richard Tucker , Inbar Mosseri , Tali Dekel , Noah Snavely

Perpetual view generation aims to synthesize a long-term video corresponding to an arbitrary camera trajectory solely from a single input image. Recent methods commonly utilize a pre-trained text-to-image diffusion model to synthesize new…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Bo Pan , Yang Chen , Yingwei Pan , Ting Yao , Wei Chen , Tao Mei

Physics-driven 4D dynamic simulation from static 3D scenes remains constrained by an overlooked contradiction: reliable motion supervision often relies on online video diffusion or optical-flow pipelines whose computational cost exceeds…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Changshe Zhang , Jie Feng , Siyu Chen , Guanbin Li , Ronghua Shang , Junpeng Zhang

Urban scene reconstruction from real-world observations has emerged as a powerful tool for self-driving development and testing. While current neural rendering approaches achieve high-fidelity rendering along the recorded trajectories,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-22 Henry Che , Jingkang Wang , Yun Chen , Ze Yang , Sivabalan Manivasagam , Raquel Urtasun

3D reconstruction and novel view synthesis are critical for validating autonomous driving systems and training advanced perception models. Recent self-supervised methods have gained significant attention due to their cost-effectiveness and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-17 Xiao Tang , Guirong Zhuo , Cong Wang , Boyuan Zheng , Minqing Huang , Lianqing Zheng , Long Chen , Shouyi Lu

Recent advances in diffusion-based video generation have opened new possibilities for controllable video editing, yet realistic video object insertion (VOI) remains challenging due to limited 4D scene understanding and inadequate handling…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Hoiyeong Jin , Hyojin Jang , Jeongho Kim , Junha Hyung , Kinam Kim , Dongjin Kim , Huijin Choi , Hyeonji Kim , Jaegul Choo

In this work, we introduce a novel approach for creating controllable dynamics in 3D-generated Gaussians using casually captured reference videos. Our method transfers the motion of objects from reference videos to a variety of generated 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-07-09 Zhoujie Fu , Jiacheng Wei , Wenhao Shen , Chaoyue Song , Xiaofeng Yang , Fayao Liu , Xulei Yang , Guosheng Lin

Despite recent advances in 3D human motion generation (MoGen) on standard benchmarks, existing text-to-motion models still face a fundamental bottleneck in their generalization capability. In contrast, adjacent generative fields, most…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Jing Lin , Ruisi Wang , Junzhe Lu , Ziqi Huang , Guorui Song , Ailing Zeng , Xian Liu , Chen Wei , Wanqi Yin , Qingping Sun , Zhongang Cai , Lei Yang , Ziwei Liu

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

The challenge of dynamic view synthesis from dynamic monocular videos, i.e., synthesizing novel views for free viewpoints given a monocular video of a dynamic scene captured by a moving camera, mainly lies in accurately modeling the…

Computer Vision and Pattern Recognition · Computer Science 2024-08-22 Meng You , Junhui Hou

The ultimate goal of video generation is to satisfy a fundamental trilemma: achieving high visual quality, maintaining rigorous physical consistency, and enabling precise controllability. While recent models can maintain this balance in…

Computer Vision and Pattern Recognition · Computer Science 2026-03-12 Tianshuo Xu , Zhifei Chen , Leyi Wu , Hao Lu , Ying-cong Chen

In this paper, we introduce \textit{DecoRec}, a novel system designed to elevate single-view 2D images to a decomposed 3D scene mesh. Current methods for single-view scene reconstruction typically rely on object retrieval or the regression…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Yuhan Ping , Yuan Liu , Xiaoxiao Long , Peng Wang , Junhui Hou , Jianyi Zheng , Jia Pan , Xin Li , Cheng Lin

Creating flexible 3D scenes from a single image is vital when direct 3D data acquisition is costly or impractical. We introduce NavCrafter, a novel framework that explores 3D scenes from a single image by synthesizing novel-view video…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Hongbo Duan , Peiyu Zhuang , Yi Liu , Zhengyang Zhang , Yuxin Zhang , Pengting Luo , Fangming Liu , Xueqian Wang

Recent advances in 3D scene reconstruction and 4D human animation have broadened adoption, but integrating the two remains difficult. Key challenges include placing humans at plausible locations and scales without interpenetration, aligning…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Qingyang Liu , Bingjie Gao , Weiheng Huang , Jun Zhang , Zhongqian Sun , Yang Wei , Fengrui Liu , Zelin Peng , Qianli Ma , Shuai Yang , Zhaohe Liao , Haonan Zhao , Li Niu

Recent progress in video generation has led to substantial improvements in visual fidelity, yet ensuring physically consistent motion remains a fundamental challenge. Intuitively, this limitation can be attributed to the fact that…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Cong Wang , Hanxin Zhu , Xiao Tang , Jiayi Luo , Xin Jin , Long Chen , Zhibo Chen

Recently, 3D reconstruction and generation have demonstrated impressive novel view synthesis results, achieving high fidelity and efficiency. However, a notable conditioning gap can be observed between these two fields, e.g., scalable 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Sibo Wu , Congrong Xu , Binbin Huang , Andreas Geiger , Anpei Chen

Scenes in the real world are often composed of several static and dynamic objects. Capturing their 4-dimensional structures, composition and spatio-temporal configuration in-the-wild, though extremely interesting, is equally hard.…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Ahmet Berke Gokmen , Ajad Chhatkuli , Luc Van Gool , Danda Pani Paudel
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