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Novel view synthesis (NVS) boosts immersive experiences in computer vision and graphics. Existing techniques, though progressed, rely on dense multi-view observations, restricting their application. This work takes on the challenge of…

Computer Vision and Pattern Recognition · Computer Science 2025-07-14 Songchun Zhang , Huiyao Xu , Sitong Guo , Zhongwei Xie , Hujun Bao , Weiwei Xu , Changqing Zou

Recent advancements in 3D generation have leveraged synthetic datasets with ground truth 3D assets and predefined cameras. However, the potential of adopting real-world datasets, which can produce significantly more realistic 3D scenes,…

Computer Vision and Pattern Recognition · Computer Science 2024-06-26 Xinyang Li , Zhangyu Lai , Linning Xu , Yansong Qu , Liujuan Cao , Shengchuan Zhang , Bo Dai , Rongrong Ji

Diffusion models have achieved remarkable progress in video generation, but their controllability remains a major limitation. Key scene factors such as layout, lighting, and camera trajectory are often entangled or only weakly modeled,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Ziqi Cai , Taoyu Yang , Zheng Chang , Si Li , Han Jiang , Shuchen Weng , Boxin Shi

Modeling scenes using video generation models has garnered growing research interest in recent years. However, most existing approaches rely on perspective video models that synthesize only limited observations of a scene, leading to issues…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Yuheng Liu , Xin Lin , Xinke Li , Baihan Yang , Chen Wang , Kalyan Sunkavalli , Yannick Hold-Geoffroy , Hao Tan , Kai Zhang , Xiaohui Xie , Zifan Shi , Yiwei Hu

With the explosive growth of video data in real-world applications, a comprehensive representation of videos becomes increasingly important. In this paper, we address the problem of video scene recognition, whose goal is to learn a…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Xuzheng Yu , Chen Jiang , Wei Zhang , Tian Gan , Linlin Chao , Jianan Zhao , Yuan Cheng , Qingpei Guo , Wei Chu

Existing video deraining methods are often trained on paired datasets, either synthetic, which limits their ability to generalize to real-world rain, or captured by static cameras, which restricts their effectiveness in dynamic scenes with…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Tuomas Varanka , Juan Luis Gonzalez , Hyeongwoo Kim , Pablo Garrido , Xu Yao

The assumption of scene rigidity is common in visual SLAM algorithms. However, it limits their applicability in populated real-world environments. Furthermore, most scenarios including autonomous driving, multi-robot collaboration and…

Robotics · Computer Science 2020-10-16 Berta Bescos , Carlos Campos , Juan D. Tardós , José Neira

Recovering 3D scenes from sparse views is a challenging task due to its inherent ill-posed problem. Conventional methods have developed specialized solutions (e.g., geometry regularization or feed-forward deterministic model) to mitigate…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Hanyang Wang , Fangfu Liu , Jiawei Chi , Yueqi Duan

Text-to-image models are showcasing the impressive ability to create high-quality and diverse generative images. Nevertheless, the transition from freehand sketches to complex scene images remains challenging using diffusion models. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-07-10 Tianyu Zhang , Xiaoxuan Xie , Xusheng Du , Haoran Xie

We present FloVD, a novel video diffusion model for camera-controllable video generation. FloVD leverages optical flow to represent the motions of the camera and moving objects. This approach offers two key benefits. Since optical flow can…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Wonjoon Jin , Qi Dai , Chong Luo , Seung-Hwan Baek , Sunghyun Cho

Recent advancements in diffusion models have greatly improved the quality and diversity of synthesized content. To harness the expressive power of diffusion models, researchers have explored various controllable mechanisms that allow users…

Computer Vision and Pattern Recognition · Computer Science 2023-04-28 Tsai-Shien Chen , Chieh Hubert Lin , Hung-Yu Tseng , Tsung-Yi Lin , Ming-Hsuan Yang

The synthesis of spatiotemporally coherent 4D content presents fundamental challenges in computer vision, requiring simultaneous modeling of high-fidelity spatial representations and physically plausible temporal dynamics. Current…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Xiaoyan Liu , Kangrui Li , Yuehao Song , Jiaxin Liu

We propose a diffusion-based approach for Text-to-Image (T2I) generation with interactive 3D layout control. Layout control has been widely studied to alleviate the shortcomings of T2I diffusion models in understanding objects' placement…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Abdelrahman Eldesokey , Peter Wonka

In this paper, we propose Scene Splatter, a momentum-based paradigm for video diffusion to generate generic scenes from single image. Existing methods, which employ video generation models to synthesize novel views, suffer from limited…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Shengjun Zhang , Jinzhao Li , Xin Fei , Hao Liu , Yueqi Duan

Generating continuous sign language videos from discrete segments is challenging due to the need for smooth transitions that preserve natural flow and meaning. Traditional approaches that simply concatenate isolated signs often result in…

Computer Vision and Pattern Recognition · Computer Science 2024-11-27 Shengeng Tang , Jiayi He , Lechao Cheng , Jingjing Wu , Dan Guo , Richang Hong

Diffusion-based \textit{image-to-video} (I2V) generation has become a central direction in generative models by turning a reference image, with optional conditions, into a temporally coherent video. Compared with broader video generation…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Xianlong Wang , Wenbo Pan , Shijia Zhou , Ke Li , Yuqi Wang , Zeyu Ye , Hangtao Zhang , Leo Yu Zhang , Xiaohua Jia

Recent advances in camera-controllable video generation have been constrained by the reliance on static-scene datasets with relative-scale camera annotations, such as RealEstate10K. While these datasets enable basic viewpoint control, they…

Computer Vision and Pattern Recognition · Computer Science 2025-04-14 Guangcong Zheng , Teng Li , Xianpan Zhou , Xi Li

Creating a vivid video from the event or scenario in our imagination is a truly fascinating experience. Recent advancements in text-to-video synthesis have unveiled the potential to achieve this with prompts only. While text is convenient…

Computer Vision and Pattern Recognition · Computer Science 2023-06-02 Jinbo Xing , Menghan Xia , Yuxin Liu , Yuechen Zhang , Yong Zhang , Yingqing He , Hanyuan Liu , Haoxin Chen , Xiaodong Cun , Xintao Wang , Ying Shan , Tien-Tsin Wong

Recent text-to-video diffusion models have achieved impressive progress. In practice, users often desire the ability to control object motion and camera movement independently for customized video creation. However, current methods lack the…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Shiyuan Yang , Liang Hou , Haibin Huang , Chongyang Ma , Pengfei Wan , Di Zhang , Xiaodong Chen , Jing Liao

Recent video-based world models have made pixel-space environments interactive at the camera level: users can navigate viewpoints while the model generates coherent visual continuations. Yet their action spaces remain incomplete: users can…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Bohai Gu , Taiyi Wu , Yueyang Yuan , Jian Liu , Xiaocheng Lu , Dazhao Du , Jie Zhang , Jinxiang Lai , Shuai Yang , Xiaotong Zhao , Alan Zhao , Song Guo
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