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Related papers: PanoWorld: Geometry-Consistent Panoramic Video Wor…

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Pano3D is a new benchmark for depth estimation from spherical panoramas. It aims to assess performance across all depth estimation traits, the primary direct depth estimation performance targeting precision and accuracy, and also the…

Computer Vision and Pattern Recognition · Computer Science 2021-09-08 Georgios Albanis , Nikolaos Zioulis , Petros Drakoulis , Vasileios Gkitsas , Vladimiros Sterzentsenko , Federico Alvarez , Dimitrios Zarpalas , Petros Daras

Recent generative models can produce high-fidelity videos, yet they often exhibit 3D spatial geometric inconsistencies. Existing evaluation methods fail to accurately characterize these inconsistencies: fidelity-centric metrics like FVD are…

Computer Vision and Pattern Recognition · Computer Science 2026-03-20 Weijia Dou , Wenzhao Zheng , Weiliang Chen , Yu Zheng , Jie Zhou , Jiwen Lu

Generating complete digital twins from videos requires precise camera control, global scene coverage, and strict spatial-temporal consistency constraints that remain challenging for perspective video generators due to their limited field of…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Ting-Hsuan Chen , Ying-Huan Chen , Tao Tu , Jie-Ying Lee , Cho-Ying Wu , Fangzhou Lin , Hengyuan Zhang , David Paz , Xinyu Huang , Yuliang Guo , Yu-Lun Liu , Yue Wang , Liu Ren

We present WonderZoom, a novel approach to generating 3D scenes with contents across multiple spatial scales from a single image. Existing 3D world generation models remain limited to single-scale synthesis and cannot produce coherent scene…

Computer Vision and Pattern Recognition · Computer Science 2025-12-11 Jin Cao , Hong-Xing Yu , Jiajun Wu

Large-scale video diffusion models achieve impressive visual quality, yet often fail to preserve geometric consistency. Prior approaches improve consistency either by augmenting the generator with additional modules or applying…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Zhaochong An , Orest Kupyn , Théo Uscidda , Andrea Colaco , Karan Ahuja , Serge Belongie , Mar Gonzalez-Franco , Marta Tintore Gazulla

Video-based world models have recently garnered increasing attention for their ability to synthesize diverse and dynamic visual environments. In this paper, we focus on shared world modeling, where a model generates multiple videos from a…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Fan Wu , Jiacheng Wei , Ruibo Li , Yi Xu , Junyou Li , Deheng Ye , Guosheng Lin

Camera-controlled video generation has achieved remarkable progress in recent years. However, existing video-to-video re-rendering methods primarily rely on Supervised Fine-Tuning using synthetic datasets. At present, there is an extreme…

Computer Vision and Pattern Recognition · Computer Science 2026-05-25 Zizun Li , Haoyu Guo , Runzhe Teng , Chunhua Shen , Tong He

World models aim to endow AI systems with the ability to represent, generate, and interact with dynamic environments in a coherent and temporally consistent manner. While recent video generation models have demonstrated impressive visual…

Multi-view image generation holds significant application value in computer vision, particularly in domains like 3D reconstruction, virtual reality, and augmented reality. Most existing methods, which rely on extending single images, face…

Computer Vision and Pattern Recognition · Computer Science 2025-11-20 Jiaqi Wu , Yaosen Chen , Shuyuan Zhu

Despite impressive progress in video generation, existing models remain limited to surface-level plausibility, lacking a coherent and unified understanding of the world. Prior approaches typically incorporate only a single form of…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Boming Tan , Xiangdong Zhang , Ning Liao , Yuqing Zhang , Shaofeng Zhang , Xue Yang , Qi Fan , Yanyong Zhang

We introduce the novel task of Pano2Vid $-$ automatic cinematography in panoramic 360$^{\circ}$ videos. Given a 360$^{\circ}$ video, the goal is to direct an imaginary camera to virtually capture natural-looking normal field-of-view (NFOV)…

Computer Vision and Pattern Recognition · Computer Science 2016-12-08 Yu-Chuan Su , Dinesh Jayaraman , Kristen Grauman

Videos inherently represent 2D projections of a dynamic 3D world. However, our analysis suggests that video diffusion models trained solely on raw video data often fail to capture meaningful geometric-aware structure in their learned…

Computer Vision and Pattern Recognition · Computer Science 2026-05-06 Haoyu Wu , Diankun Wu , Tianyu He , Junliang Guo , Yang Ye , Yueqi Duan , Jiang Bian

Existing diffusion-based 3D scene generation methods primarily operate in 2D image/video latent spaces, which makes maintaining cross-view appearance and geometric consistency inherently challenging. To bridge this gap, we present OneWorld,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Sensen Gao , Zhaoqing Wang , Qihang Cao , Dongdong Yu , Changhu Wang , Tongliang Liu , Mingming Gong , Jiawang Bian

Despite remarkable advancements in video depth estimation, existing methods exhibit inherent limitations in achieving geometric fidelity through the affine-invariant predictions, limiting their applicability in reconstruction and other…

Graphics · Computer Science 2025-04-02 Tian-Xing Xu , Xiangjun Gao , Wenbo Hu , Xiaoyu Li , Song-Hai Zhang , Ying Shan

Understanding geometric, semantic, and instance information in 3D scenes from sequential video data is essential for applications in robotics and augmented reality. However, existing Simultaneous Localization and Mapping (SLAM) methods…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Runnan Chen , Zhaoqing Wang , Jiepeng Wang , Yuexin Ma , Mingming Gong , Wenping Wang , Tongliang Liu

Tremendous progress in visual scene generation now turns a single image into an explorable 3D world, yet immersion remains incomplete without sound. We introduce Image2AVScene, the task of generating a 3D audio-visual scene from a single…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Derong Jin , Xiyi Chen , Ming C. Lin , Ruohan Gao

Generating 3D scenes is still a challenging task due to the lack of readily available scene data. Most existing methods only produce partial scenes and provide limited navigational freedom. We introduce a practical and scalable solution…

Graphics · Computer Science 2025-09-26 Zhaoyang Zhang , Yannick Hold-Geoffroy , Miloš Hašan , Ziwen Chen , Fujun Luan , Julie Dorsey , Yiwei Hu

Text-based 2D diffusion models have demonstrated impressive capabilities in image generation and editing. Meanwhile, the 2D diffusion models also exhibit substantial potentials for 3D editing tasks. However, how to achieve consistent edits…

Computer Vision and Pattern Recognition · Computer Science 2024-06-26 Ruihuang Li , Liyi Chen , Zhengqiang Zhang , Varun Jampani , Vishal M. Patel , Lei Zhang

With the advent of portable 360{\deg} cameras, panorama has gained significant attention in applications like virtual reality (VR), virtual tours, robotics, and autonomous driving. As a result, wide-baseline panorama view synthesis has…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Cheng Zhang , Haofei Xu , Qianyi Wu , Camilo Cruz Gambardella , Dinh Phung , Jianfei Cai

Video world models aim to simulate dynamic, real-world environments, yet existing methods struggle to provide unified and precise control over camera and multi-object motion, as videos inherently capture dynamics in the projected 2D image…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Sixiao Zheng , Minghao Yin , Wenbo Hu , Xiaoyu Li , Ying Shan , Yanwei Fu