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Camera control, which achieves diverse visual effects by changing camera position and pose, has attracted widespread attention. However, existing methods face challenges such as complex interaction and limited control capabilities. To…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Xiaoda Yang , Jiayang Xu , Kaixuan Luan , Xinyu Zhan , Hongshun Qiu , Shijun Shi , Hao Li , Shuai Yang , Li Zhang , Checheng Yu , Cewu Lu , Lixin Yang

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

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

Video fundamentally intertwines two crucial axes: the dynamic content of a scene and the camera motion through which it is observed. However, existing generation models often entangle these factors, limiting independent control. In this…

Computer Vision and Pattern Recognition · Computer Science 2026-04-08 Yukun Wang , Ruihuang Li , Jiale Tao , Shiyuan Yang , Liyi Chen , Zhantao Yang , Handz , Yulan Guo , Shuai Shao , Qinglin Lu

Autonomous driving world models are expected to work effectively across three core dimensions: state, action, and reward. Existing models, however, are typically restricted to limited state modalities, short video sequences, imprecise…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Bohan Li , Zhuang Ma , Dalong Du , Baorui Peng , Zhujin Liang , Zhenqiang Liu , Chao Ma , Yueming Jin , Hao Zhao , Wenjun Zeng , Xin Jin

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

Real-world applications like video gaming and virtual reality often demand the ability to model 3D scenes that users can explore along custom camera trajectories. While significant progress has been made in generating 3D objects from text…

Computer Vision and Pattern Recognition · Computer Science 2025-06-05 Tianyu Huang , Wangguandong Zheng , Tengfei Wang , Yuhao Liu , Zhenwei Wang , Junta Wu , Jie Jiang , Hui Li , Rynson W. H. Lau , Wangmeng Zuo , Chunchao Guo

As virtual reality gains popularity, the demand for controllable creation of immersive and dynamic omnidirectional videos (ODVs) is increasing. While previous text-to-ODV generation methods achieve impressive results, they struggle with…

Computer Vision and Pattern Recognition · Computer Science 2024-12-13 Weiqi Li , Shijie Zhao , Chong Mou , Xuhan Sheng , Zhenyu Zhang , Qian Wang , Junlin Li , Li Zhang , Jian Zhang

We introduce the problem of perpetual view generation - long-range generation of novel views corresponding to an arbitrarily long camera trajectory given a single image. This is a challenging problem that goes far beyond the capabilities of…

Computer Vision and Pattern Recognition · Computer Science 2021-12-02 Andrew Liu , Richard Tucker , Varun Jampani , Ameesh Makadia , Noah Snavely , Angjoo Kanazawa

Panoramic video generation has attracted growing attention due to its applications in virtual reality and immersive media. However, existing methods lack explicit motion control and struggle to generate scenes with large and complex…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Cheng Zhang , Hanwen Liang , Donny Y. Chen , Qianyi Wu , Konstantinos N. Plataniotis , Camilo Cruz Gambardella , Jianfei Cai

Recent advancements in video generation have primarily leveraged diffusion models for short-duration content. However, these approaches often fall short in modeling complex narratives and maintaining character consistency over extended…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Canyu Zhao , Mingyu Liu , Wen Wang , Weihua Chen , Fan Wang , Hao Chen , Bo Zhang , Chunhua Shen

Generating a complete and explorable 360-degree visual world enables a wide range of downstream applications. While prior works have advanced the field, they remain constrained by either narrow field-of-view limitations, which hinder the…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Yuyang Yin , HaoXiang Guo , Fangfu Liu , Mengyu Wang , Hanwen Liang , Eric Li , Yikai Wang , Xiaojie Jin , Yao Zhao , Yunchao Wei

Producing long, coherent video sequences with stable 3D structure remains a major challenge, particularly in streaming scenarios. Motivated by this, we introduce Endless World, a real-time framework for infinite, 3D-consistent video…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Ke Zhang , Yiqun Mei , Jiacong Xu , Vishal M. Patel

Generative video modeling has made significant strides, yet ensuring structural and temporal consistency over long sequences remains a challenge. Current methods predominantly rely on RGB signals, leading to accumulated errors in object…

Computer Vision and Pattern Recognition · Computer Science 2025-08-22 Zhiheng Liu , Xueqing Deng , Shoufa Chen , Angtian Wang , Qiushan Guo , Mingfei Han , Zeyue Xue , Mengzhao Chen , Ping Luo , Linjie Yang

End-to-end autonomous driving aims to generate safe and plausible planning policies from raw sensor input. Driving world models have shown great potential in learning rich representations by predicting the future evolution of a driving…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Xingtai Gui , Meijie Zhang , Tianyi Yan , Wencheng Han , Jiahao Gong , Feiyang Tan , Cheng-zhong Xu , Jianbing Shen

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

Generating 3D worlds from text is a highly anticipated goal in computer vision. Existing works are limited by the degree of exploration they allow inside of a scene, i.e., produce streched-out and noisy artifacts when moving beyond central…

Computer Vision and Pattern Recognition · Computer Science 2025-09-17 Manuel-Andreas Schneider , Lukas Höllein , Matthias Nießner

There are two prevalent ways to constructing 3D scenes: procedural generation and 2D lifting. Among them, panorama-based 2D lifting has emerged as a promising technique, leveraging powerful 2D generative priors to produce immersive,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-31 Yukun Huang , Jiwen Yu , Yanning Zhou , Jianan Wang , Xintao Wang , Pengfei Wan , Xihui Liu

Recent advances in text-to-3D scene generation have demonstrated significant potential to transform content creation across multiple industries. Although the research community has made impressive progress in addressing the challenges of…

Prior approaches injecting camera control into diffusion models have focused on specific subsets of 4D consistency tasks: novel view synthesis, text-to-video with camera control, image-to-video, amongst others. Therefore, these fragmented…

Computer Vision and Pattern Recognition · Computer Science 2026-01-26 Xiang Fan , Sharath Girish , Vivek Ramanujan , Chaoyang Wang , Ashkan Mirzaei , Petr Sushko , Aliaksandr Siarohin , Sergey Tulyakov , Ranjay Krishna
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