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Panoramic video generation aims to synthesize 360-degree immersive videos, holding significant importance in the fields of VR, world models, and spatial intelligence. Existing works fail to synthesize high-quality panoramic videos due to…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Zixun Fang , Kai Zhu , Zhiheng Liu , Yu Liu , Wei Zhai , Yang Cao , Zheng-Jun Zha

Video is a rich and scalable source of 3D/4D visual observations, and camera control is a key capability for video generation models to produce geometrically meaningful content. Existing approaches typically learn a mapping from camera…

Computer Vision and Pattern Recognition · Computer Science 2026-05-15 Chen Hou , Christian Rupprecht

Video Diffusion Models have been developed for video generation, usually integrating text and image conditioning to enhance control over the generated content. Despite the progress, ensuring consistency across frames remains a challenge,…

Computer Vision and Pattern Recognition · Computer Science 2024-11-12 Tian Xia , Xuweiyi Chen , Sihan Xu

Diffusion models have achieved remarkable success across various domains. However, their slow generation speed remains a critical challenge. Existing acceleration methods, while aiming to reduce steps, often compromise sample quality,…

Machine Learning · Computer Science 2025-03-26 Huiyang Shao , Xin Xia , Yuhong Yang , Yuxi Ren , Xing Wang , Xuefeng Xiao

Generating motion-controlled videos--where user-specified actions drive physically plausible scene dynamics under freely chosen viewpoints--demands two capabilities: (1) disentangled motion control, allowing users to separately control the…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Shaowei Liu , Xuanchi Ren , Tianchang Shen , Huan Ling , Saurabh Gupta , Shenlong Wang , Sanja Fidler , Jun Gao

Vision-centric autonomous driving systems require diverse data for robust training and evaluation, which can be augmented by manipulating object positions and appearances within existing scene captures. While recent advancements in…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Yiyuan Liang , Zhiying Yan , Liqun Chen , Jiahuan Zhou , Luxin Yan , Sheng Zhong , Xu Zou

Maritime vessel maneuvers, characterized by their inherent complexity and indeterminacy, requires vessel trajectory prediction system capable of modeling the multi-modality nature of future motion states. Conventional stochastic trajectory…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Changlin Li , Yanglei Gan , Tian Lan , Yuxiang Cai , Xueyi Liu , Run Lin , Qiao Liu

Stereo video generation has been gaining increasing attention with recent advancements in video diffusion models. However, most existing methods focus on generating 3D stereoscopic videos from monocular 2D videos. These approaches typically…

Computer Vision and Pattern Recognition · Computer Science 2025-06-09 Xingchang Huang , Ashish Kumar Singh , Florian Dubost , Cristina Nader Vasconcelos , Sakar Khattar , Liang Shi , Christian Theobalt , Cengiz Oztireli , Gurprit Singh

Recent advancements in video diffusion models have shown exceptional abilities in simulating real-world dynamics and maintaining 3D consistency. This progress inspires us to investigate the potential of these models to ensure dynamic…

Computer Vision and Pattern Recognition · Computer Science 2024-12-11 Jianhong Bai , Menghan Xia , Xintao Wang , Ziyang Yuan , Xiao Fu , Zuozhu Liu , Haoji Hu , Pengfei Wan , Di Zhang

Diffusion models have recently emerged as powerful tools for camera simulation, enabling both geometric transformations and realistic optical effects. Among these, image-based bokeh rendering has shown promising results, but diffusion for…

Computer Vision and Pattern Recognition · Computer Science 2025-10-13 Yang Yang , Siming Zheng , Qirui Yang , Jinwei Chen , Boxi Wu , Xiaofei He , Deng Cai , Bo Li , Peng-Tao Jiang

Video restoration aims to reconstruct high quality video sequences from low quality inputs, addressing tasks such as super resolution, denoising, and deblurring. Traditional regression based methods often produce unrealistic details and…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Sicheng Gao , Nancy Mehta , Zongwei Wu , Radu Timofte

Recent advances in video diffusion models have significantly improved character animation techniques. However, current approaches rely on basic structural conditions such as DWPose or SMPL-X to animate character images, limiting their…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Muyao Niu , Mingdeng Cao , Yifan Zhan , Qingtian Zhu , Mingze Ma , Jiancheng Zhao , Yanhong Zeng , Zhihang Zhong , Xiao Sun , Yinqiang Zheng

We present a method for generating Streetscapes-long sequences of views through an on-the-fly synthesized city-scale scene. Our generation is conditioned by language input (e.g., city name, weather), as well as an underlying map/layout…

Computer Vision and Pattern Recognition · Computer Science 2024-07-26 Boyang Deng , Richard Tucker , Zhengqi Li , Leonidas Guibas , Noah Snavely , Gordon Wetzstein

Current motion-conditioned video generation methods suffer from prohibitive latency (minutes per video) and non-causal processing that prevents real-time interaction. We present MotionStream, enabling sub-second latency with up to 29 FPS…

Computer Vision and Pattern Recognition · Computer Science 2026-03-06 Joonghyuk Shin , Zhengqi Li , Richard Zhang , Jun-Yan Zhu , Jaesik Park , Eli Shechtman , Xun Huang

Recent Text-to-Video (T2V) models have demonstrated powerful capability in visual simulation of real-world geometry and physical laws, indicating its potential as implicit world models. Inspired by this, we explore the feasibility of…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Yu Li , Menghan Xia , Gongye Liu , Jianhong Bai , Xintao Wang , Conglang Zhang , Yuxuan Lin , Ruihang Chu , Pengfei Wan , Yujiu Yang

Recent advances in diffusion models have improved controllable streetscape generation and supported downstream perception and planning tasks. However, challenges remain in accurately modeling driving scenes and generating long videos. To…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Jianbiao Mei , Tao Hu , Xuemeng Yang , Licheng Wen , Yu Yang , Tiantian Wei , Yukai Ma , Min Dou , Botian Shi , Yong Liu

Generative world models have become essential data engines for autonomous driving, yet most existing efforts focus on videos or occupancy grids, overlooking the unique LiDAR properties. Extending LiDAR generation to dynamic 4D world…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Ao Liang , Youquan Liu , Yu Yang , Dongyue Lu , Linfeng Li , Lingdong Kong , Huaici Zhao , Wei Tsang Ooi

LiDAR-based 3D single object tracking (3D SOT) is a critical task in robotics and autonomous systems. Existing methods typically follow frame-wise motion estimation or a sequence-based paradigm. However, the two-frame methods are efficient…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 BaiChen Fan , Yuanxi Cui , Jian Li , Qin Wang , Shibo Zhao , Muqing Cao , Sifan Zhou

Multi-view or 4D video generation has emerged as a significant research topic. Nonetheless, recent approaches to 4D generation still struggle with fundamental limitations, as they primarily rely on harnessing multiple video diffusion models…

Computer Vision and Pattern Recognition · Computer Science 2025-12-05 Jangho Park , Taesung Kwon , Jong Chul Ye

Generating long and consistent videos has emerged as a significant yet challenging problem. While most existing diffusion-based video generation models, derived from image generation models, demonstrate promising performance in generating…

Computer Vision and Pattern Recognition · Computer Science 2024-04-30 Yichen Ouyang , jianhao Yuan , Hao Zhao , Gaoang Wang , Bo zhao