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We present PanoWorld, a panoramic video world model that generates geometry-consistent 360$\degree$ video from a single image and a caption. Existing panoramic video methods optimize primarily for visual realism and do not explicitly…

Computer Vision and Pattern Recognition · Computer Science 2026-05-18 Le Jiang , Xiangyu Bai , Bishoy Galoaa , Shayda Moezzi , Caleb James Lee , Tooba Imtiaz , Edmund Yeh , Jennifer Dy , Yanzhi Wang , Sarah Ostadabbas

Advancements in 3D scene reconstruction have transformed 2D images from the real world into 3D models, producing realistic 3D results from hundreds of input photos. Despite great success in dense-view reconstruction scenarios, rendering a…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Fangfu Liu , Wenqiang Sun , Hanyang Wang , Yikai Wang , Haowen Sun , Junliang Ye , Jun Zhang , Yueqi Duan

3D assets are essential in the digital age. While automatic 3D generation, such as image-to-3d, has made significant strides in recent years, it often struggles to achieve fast, detailed, and high-fidelity generation simultaneously. In this…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Huanning Dong , Yinuo Huang , Fan Li , Ping Kuang

Synthesizing photo-realistic visual observations from an ego vehicle's driving trajectory is a critical step towards scalable training of self-driving models. Reconstruction-based methods create 3D scenes from driving logs and synthesize…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Jiageng Mao , Boyi Li , Boris Ivanovic , Yuxiao Chen , Yan Wang , Yurong You , Chaowei Xiao , Danfei Xu , Marco Pavone , Yue Wang

Existing 3D-aware image synthesis approaches mainly focus on generating a single canonical object and show limited capacity in composing a complex scene containing a variety of objects. This work presents DisCoScene: a 3Daware generative…

Computer Vision and Pattern Recognition · Computer Science 2022-12-23 Yinghao Xu , Menglei Chai , Zifan Shi , Sida Peng , Ivan Skorokhodov , Aliaksandr Siarohin , Ceyuan Yang , Yujun Shen , Hsin-Ying Lee , Bolei Zhou , Sergey Tulyakov

Video diffusion models generate high-quality and diverse worlds; however, individual frames often lack 3D consistency across the output sequence, which makes the reconstruction of 3D worlds difficult. To this end, we propose a new method…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Lukas Höllein , Matthias Nießner

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

In this work, we present SceneDreamer, an unconditional generative model for unbounded 3D scenes, which synthesizes large-scale 3D landscapes from random noise. Our framework is learned from in-the-wild 2D image collections only, without…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Zhaoxi Chen , Guangcong Wang , Ziwei Liu

We tackle a new problem: generating geometrically consistent multi-view scenes from a single freehand sketch. Freehand sketches are the most geometrically impoverished input one could offer a multi-view generator. They convey scene intent…

Computer Vision and Pattern Recognition · Computer Science 2026-04-17 Ahmed Bourouis , Savas Ozkan , Andrea Maracani , Yi-Zhe Song , Mete Ozay

Panorama synthesis endeavors to craft captivating 360-degree visual landscapes, immersing users in the heart of virtual worlds. Nevertheless, contemporary panoramic synthesis techniques grapple with the challenge of semantically guiding the…

Computer Vision and Pattern Recognition · Computer Science 2024-01-30 Kun Yan , Lei Ji , Chenfei Wu , Jian Liang , Ming Zhou , Nan Duan , Shuai Ma

Recent advances in diffusion models have revolutionized 2D and 3D content creation, yet generating photorealistic dynamic 4D scenes remains a significant challenge. Existing dynamic 4D generation methods typically rely on distilling…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Vinayak Gupta , Yunze Man , Yu-Xiong Wang

World generation is a fundamental capability for applications like video games, simulation, and robotics. However, existing approaches face three main obstacles: controllability, scalability, and efficiency. End-to-end scene generation…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Han-Hung Lee , Cheng-Yu Yang , Yu-Lun Liu , Angel X. Chang

In this work, we introduce Unique3D, a novel image-to-3D framework for efficiently generating high-quality 3D meshes from single-view images, featuring state-of-the-art generation fidelity and strong generalizability. Previous methods based…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Kailu Wu , Fangfu Liu , Zhihan Cai , Runjie Yan , Hanyang Wang , Yating Hu , Yueqi Duan , Kaisheng Ma

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

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

3D scene generation has long been dominated by 2D multi-view or video diffusion models. This is due not only to the lack of scene-level 3D latent representation, but also to the fact that most scene-level 3D visual data exists in the form…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Dongxu Wei , Qi Xu , Zhiqi Li , Hangning Zhou , Cong Qiu , Hailong Qin , Mu Yang , Zhaopeng Cui , Peidong 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

We present DreamWaltz, a novel framework for generating and animating complex 3D avatars given text guidance and parametric human body prior. While recent methods have shown encouraging results for text-to-3D generation of common objects,…

Computer Vision and Pattern Recognition · Computer Science 2023-11-07 Yukun Huang , Jianan Wang , Ailing Zeng , He Cao , Xianbiao Qi , Yukai Shi , Zheng-Jun Zha , Lei Zhang

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 years have seen remarkable progress in deep learning powered visual content creation. This includes deep generative 3D-aware image synthesis, which produces high-idelity images in a 3D-consistent manner while simultaneously capturing…

Computer Vision and Pattern Recognition · Computer Science 2023-10-04 Weihao Xia , Jing-Hao Xue
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