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Interactive Generative Video (IGV) has emerged as a crucial technology in response to the growing demand for high-quality, interactive video content across various domains. In this paper, we define IGV as a technology that combines…

Computer Vision and Pattern Recognition · Computer Science 2025-05-01 Jiwen Yu , Yiran Qin , Haoxuan Che , Quande Liu , Xintao Wang , Pengfei Wan , Di Zhang , Kun Gai , Hao Chen , Xihui Liu

Interactive video generation has significant potential for scene simulation and video creation. However, existing methods often struggle with maintaining scene consistency during long video generation under dynamic camera control due to…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Xinhang Gao , Junlin Guan , Shuhan Luo , Wenzhuo Li , Guanghuan Tan , Jiacheng Wang

Embodied AI and robotic systems increasingly depend on scalable, diverse, and physically grounded 3D content for simulation-based training and real-world deployment. While 3D generative modeling has advanced rapidly, embodied applications…

Robotics · Computer Science 2026-05-11 Tianwei Ye , Yifan Mao , Minwen Liao , Jian Liu , Chunchao Guo , Dazhao Du , Quanxin Shou , Fangqi Zhu , Song Guo

Building video world models upon pretrained video generation systems represents an important yet challenging step toward general spatiotemporal intelligence. A world model should possess three essential properties: controllability,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Jianxiong Gao , Zhaoxi Chen , Xian Liu , Junhao Zhuang , Chengming Xu , Jianfeng Feng , Yu Qiao , Yanwei Fu , Chenyang Si , Ziwei Liu

In the world of technology and AI, digital models play an important role in our lives and are an essential part of the digital twins of real-world objects. They can be created by designers, artists, or game developers using spline curves…

Graphics · Computer Science 2025-05-20 Rushan Ziatdinov , Rifkat Nabiyev

Unbounded 3D world generation is emerging as a foundational task for scene modeling in computer vision, graphics, and robotics. In this work, we present WorldFlow3D, a novel method capable of generating unbounded 3D worlds. Building upon a…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Amogh Joshi , Julian Ost , Felix Heide

Recent video generation models have achieved remarkable progress and are now deployed in film, social media production, and advertising. Beyond their creative potential, such models also hold promise as world simulators for robotics and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 David Romero , Ariana Bermudez , Viacheslav Iablochnikov , Hao Li , Fabio Pizzati , Ivan Laptev

Constrained generative modeling is fundamental to applications such as robotic control and autonomous driving, where models must respect physical laws and safety-critical constraints. In real-world settings, these constraints rarely take…

Machine Learning · Computer Science 2026-03-10 Xiaoxuan Liang , Saeid Naderiparizi , Yunpeng Liu , Berend Zwartsenberg , Frank Wood

Explorable 3D world generation from a single image or text prompt forms a cornerstone of spatial intelligence. Recent works utilize video model to achieve wide-scope and generalizable 3D world generation. However, existing approaches often…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Zhongqi Yang , Wenhang Ge , Yuqi Li , Jiaqi Chen , Haoyuan Li , Mengyin An , Fei Kang , Hua Xue , Baixin Xu , Yuyang Yin , Eric Li , Yang Liu , Yikai Wang , Hao-Xiang Guo , Yahui Zhou

With the rapid advancement in video generation, people can conveniently use video generation models to create videos tailored to their specific desires. As a result, there are also growing concerns about the potential misuse of video…

Cryptography and Security · Computer Science 2025-07-08 Yan Pang , Baicheng Chen , Yang Zhang , Tianhao Wang

World models serve as core simulators for fields such as agentic AI, embodied AI, and gaming, capable of generating long, physically realistic, and interactive high-quality videos. Moreover, scaling these models could unlock emergent…

Computer Vision and Pattern Recognition · Computer Science 2026-04-30 Inferix Team , Tianyu Feng , Yizeng Han , Jiahao He , Yuanyu He , Xi Lin , Teng Liu , Hanfeng Lu , Jiasheng Tang , Wei Wang , Zhiyuan Wang , Jichao Wu , Mingyang Yang , Yinghao Yu , Zeyu Zhang , Bohan Zhuang

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

We present an efficient text-to-video generation framework based on latent diffusion models, termed MagicVideo. MagicVideo can generate smooth video clips that are concordant with the given text descriptions. Due to a novel and efficient 3D…

Computer Vision and Pattern Recognition · Computer Science 2023-05-12 Daquan Zhou , Weimin Wang , Hanshu Yan , Weiwei Lv , Yizhe Zhu , Jiashi Feng

Video generation models have significantly advanced embodied intelligence, unlocking new possibilities for generating diverse robot data that capture perception, reasoning, and action in the physical world. However, synthesizing…

Computer Vision and Pattern Recognition · Computer Science 2026-01-22 Yufan Deng , Zilin Pan , Hongyu Zhang , Xiaojie Li , Ruoqing Hu , Yufei Ding , Yiming Zou , Yan Zeng , Daquan Zhou

While image manipulation achieves tremendous breakthroughs (e.g., generating realistic faces) in recent years, video generation is much less explored and harder to control, which limits its applications in the real world. For instance,…

Computer Vision and Pattern Recognition · Computer Science 2019-08-08 Tsun-Hsuan Wang , Yen-Chi Cheng , Chieh Hubert Lin , Hwann-Tzong Chen , Min Sun

Predicting future video frames is extremely challenging, as there are many factors of variation that make up the dynamics of how frames change through time. Previously proposed solutions require complex inductive biases inside network…

Computer Vision and Pattern Recognition · Computer Science 2019-11-06 Ruben Villegas , Arkanath Pathak , Harini Kannan , Dumitru Erhan , Quoc V. Le , Honglak Lee

Trained on internet-scale video data, generative world models are increasingly recognized as powerful world simulators that can generate consistent and plausible dynamics over structure, motion, and physics. This raises a natural question:…

Computer Vision and Pattern Recognition · Computer Science 2025-10-02 Kevin Zhang , Kuangzhi Ge , Xiaowei Chi , Renrui Zhang , Shaojun Shi , Zhen Dong , Sirui Han , Shanghang Zhang

3D world generation is essential for applications such as immersive content creation or autonomous driving simulation. Recent advances in 3D world generation have shown promising results; however, these methods are constrained by grid…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Jaeyoung Chung , Suyoung Lee , Jianfeng Xiang , Jiaolong Yang , Kyoung Mu Lee

The flourishing of video generation technologies has endangered the credibility of real-world information and intensified the demand for AI-generated video detectors. Despite some progress, the lack of high-quality real-world datasets…

Computer Vision and Pattern Recognition · Computer Science 2025-06-13 Weiliang Chen , Wenzhao Zheng , Yu Zheng , Lei Chen , Jie Zhou , Jiwen Lu , Yueqi Duan

The landscape of computer graphics has undergone significant transformations with the recent advances of differentiable rendering models. These rendering models often rely on heuristic designs that may not fully align with the final…

Computer Vision and Pattern Recognition · Computer Science 2024-12-09 Fangneng Zhan , Hanxue Liang , Yifan Wang , Michael Niemeyer , Michael Oechsle , Adam Kortylewski , Cengiz Oztireli , Gordon Wetzstein , Christian Theobalt