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This study introduces an efficient and effective method, MeDM, that utilizes pre-trained image Diffusion Models for video-to-video translation with consistent temporal flow. The proposed framework can render videos from scene position…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Ernie Chu , Tzuhsuan Huang , Shuo-Yen Lin , Jun-Cheng Chen

Video world models can generate realistic futures from a single instruction, but they often fail to preserve consistent point-level motion over time. As a result, the generated videos appear plausible, yet lack the physical grounding…

Computer Vision and Pattern Recognition · Computer Science 2026-05-25 Kaichen Zhou , Yuzhen Chen , Fangneng Zhan , Hang Hua , Grace Chen , Xinhai Chang , Ao Qu , Yilun Du , Zhuang Liu , Paul Pu Liang , Mengyu Wang

Video generation models (VGMs) have received extensive attention recently and serve as promising candidates for general-purpose large vision models. While they can only generate short videos each time, existing methods achieve long video…

Computer Vision and Pattern Recognition · Computer Science 2024-12-13 Yuanhui Huang , Wenzhao Zheng , Yuan Gao , Xin Tao , Pengfei Wan , Di Zhang , Jie Zhou , Jiwen Lu

While video-generation-based embodied world models have gained increasing attention, their reliance on large-scale embodied interaction data remains a key bottleneck. The scarcity, difficulty of collection, and high dimensionality of…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Hao Li , Qiao Sun

Generative artificial intelligence has recently progressed from static image and video synthesis to 3D content generation, culminating in the emergence of 4D generation-the task of synthesizing temporally coherent dynamic 3D assets guided…

Computer Vision and Pattern Recognition · Computer Science 2025-07-25 Qiaowei Miao , Kehan Li , Jinsheng Quan , Zhiyuan Min , Shaojie Ma , Yichao Xu , Yi Yang , Ping Liu , Yawei Luo

Recent advancements in 3D generation are predominantly propelled by improvements in 3D-aware image diffusion models. These models are pretrained on Internet-scale image data and fine-tuned on massive 3D data, offering the capability of…

Computer Vision and Pattern Recognition · Computer Science 2024-10-03 Zeyu Yang , Zijie Pan , Chun Gu , Li 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

Existing multimodal generative models fall short as qualified design copilots, as they often struggle to generate imaginative outputs once instructions are less detailed or lack the ability to maintain consistency with the provided…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Zhipeng Huang , Shaobin Zhuang , Canmiao Fu , Binxin Yang , Ying Zhang , Chong Sun , Zhizheng Zhang , Yali Wang , Chen Li , Zheng-Jun Zha

Action-conditioned robot world models generate future video frames of the manipulated scene given a robot action sequence, offering a promising alternative for simulating tasks that are difficult to model with traditional physics engines.…

Robotics · Computer Science 2026-03-27 Jai Bardhan , Patrik Drozdik , Josef Sivic , Vladimir Petrik

This paper presents ShareVerse, a video generation framework enabling multi-agent shared world modeling, addressing the gap in existing works that lack support for unified shared world construction with multi-agent interaction. ShareVerse…

Computer Vision and Pattern Recognition · Computer Science 2026-03-04 Jiayi Zhu , Jianing Zhang , Yiying Yang , Wei Cheng , Xiaoyun Yuan

The Metaverse represents a transformative shift beyond traditional mobile Internet, creating an immersive, persistent digital ecosystem where users can interact, socialize, and work within 3D virtual environments. Powered by large models…

Computers and Society · Computer Science 2025-08-12 Yuntao Wang , Qinnan Hu , Zhou Su , Linkang Du , Qichao Xu , Weiwei Li

Recent advancements in diffusion models have set new benchmarks in image and video generation, enabling realistic visual synthesis across single- and multi-frame contexts. However, these models still struggle with efficiently and explicitly…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Qihang Zhang , Shuangfei Zhai , Miguel Angel Bautista , Kevin Miao , Alexander Toshev , Joshua Susskind , Jiatao Gu

The field of generative models has recently witnessed significant progress, with diffusion models showing remarkable performance in image generation. In light of this success, there is a growing interest in exploring the application of…

Computer Vision and Pattern Recognition · Computer Science 2023-06-21 Ariel Lapid , Idan Achituve , Lior Bracha , Ethan Fetaya

Recent approaches have demonstrated the promise of using diffusion models to generate interactive and explorable worlds. However, most of these methods face critical challenges such as excessively large parameter sizes, reliance on lengthy…

Computer Vision and Pattern Recognition · Computer Science 2025-12-29 Xiaofeng Mao , Zhen Li , Chuanhao Li , Xiaojie Xu , Kaining Ying , Tong He , Jiangmiao Pang , Yu Qiao , Kaipeng Zhang

The ability to automatically generate large-scale, interactive, and physically realistic 3D environments is crucial for advancing robotic learning and embodied intelligence. However, existing generative approaches often fail to capture the…

Computer Vision and Pattern Recognition · Computer Science 2026-01-19 ChunTeng Chen , YiChen Hsu , YiWen Liu , WeiFang Sun , TsaiChing Ni , ChunYi Lee , Min Sun , YuanFu Yang

Achieving reliable and efficient planning in complex driving environments requires a model that can reason over the scene's geometry, appearance, and dynamics. We present UniDWM, a unified driving world model that advances autonomous…

Robotics · Computer Science 2026-02-03 Shuai Liu , Siheng Ren , Xiaoyao Zhu , Quanmin Liang , Zefeng Li , Qiang Li , Xin Hu , Kai Huang

Embodied world models aim to predict and interact with the physical world through visual observations and actions. However, existing models struggle to accurately translate low-level actions (e.g., joint positions) into precise robotic…

Robotics · Computer Science 2026-04-01 Taiyi Su , Jian Zhu , Yaxuan Li , Chong Ma , Jianjun Zhang , Zitai Huang , Hanli Wang , Yi Xu

Recent 3D large reconstruction models typically employ a two-stage process, including first generate multi-view images by a multi-view diffusion model, and then utilize a feed-forward model to reconstruct images to 3D content.However,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Zhenyu Tang , Junwu Zhang , Xinhua Cheng , Wangbo Yu , Chaoran Feng , Yatian Pang , Bin Lin , Li Yuan

We present 4DNeX, the first feed-forward framework for generating 4D (i.e., dynamic 3D) scene representations from a single image. In contrast to existing methods that rely on computationally intensive optimization or require multi-frame…

Computer Vision and Pattern Recognition · Computer Science 2025-08-19 Zhaoxi Chen , Tianqi Liu , Long Zhuo , Jiawei Ren , Zeng Tao , He Zhu , Fangzhou Hong , Liang Pan , Ziwei Liu

World models have become crucial for autonomous driving, as they learn how scenarios evolve over time to address the long-tail challenges of the real world. However, current approaches relegate world models to limited roles: they operate…

Computer Vision and Pattern Recognition · Computer Science 2026-04-20 Tianze Xia , Yongkang Li , Lijun Zhou , Jingfeng Yao , Kaixin Xiong , Haiyang Sun , Bing Wang , Kun Ma , Guang Chen , Hangjun Ye , Wenyu Liu , Xinggang Wang