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This paper presents a novel framework for converting 2D videos to immersive stereoscopic 3D, addressing the growing demand for 3D content in immersive experience. Leveraging foundation models as priors, our approach overcomes the…

Computer Vision and Pattern Recognition · Computer Science 2024-09-12 Sijie Zhao , Wenbo Hu , Xiaodong Cun , Yong Zhang , Xiaoyu Li , Zhe Kong , Xiangjun Gao , Muyao Niu , Ying Shan

The demand for stereo images increases as manufacturers launch more XR devices. To meet this demand, we introduce StereoDiffusion, a method that, unlike traditional inpainting pipelines, is trainning free, remarkably straightforward to use,…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Lezhong Wang , Jeppe Revall Frisvad , Mark Bo Jensen , Siavash Arjomand Bigdeli

Stereo images are fundamental to numerous applications, including extended reality (XR) devices, autonomous driving, and robotics. Unfortunately, acquiring high-quality stereo images remains challenging due to the precise calibration…

Computer Vision and Pattern Recognition · Computer Science 2025-07-15 Feng Qiao , Zhexiao Xiong , Eric Xing , Nathan Jacobs

Generating high-quality stereo videos requires consistent depth perception and temporal coherence across frames. Despite advances in image and video synthesis using diffusion models, producing high-quality stereo videos remains a…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Jian Shi , Qian Wang , Zhenyu Li , Wenqing Cui , Ramzi Idoughi , Peter Wonka

Video generation has achieved remarkable progress with the introduction of diffusion models, which have significantly improved the quality of generated videos. However, recent research has primarily focused on scaling up model training,…

Computer Vision and Pattern Recognition · Computer Science 2025-01-16 Chenyang Si , Weichen Fan , Zhengyao Lv , Ziqi Huang , Yu Qiao , Ziwei Liu

We present StereoWorld, a camera-conditioned stereo world model that jointly learns appearance and binocular geometry for end-to-end stereo video generation.Unlike monocular RGB or RGBD approaches, StereoWorld operates exclusively within…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Yang-Tian Sun , Zehuan Huang , Yifan Niu , Lin Ma , Yan-Pei Cao , Yuewen Ma , Xiaojuan Qi

State-of-the-art supervised stereo matching methods have achieved remarkable performance on various benchmarks. However, their generalization to real-world scenarios remains challenging due to the scarcity of annotated real-world stereo…

Computer Vision and Pattern Recognition · Computer Science 2025-07-30 Xianqi Wang , Hao Yang , Gangwei Xu , Junda Cheng , Min Lin , Yong Deng , Jinliang Zang , Yurui Chen , Xin Yang

The rising popularity of immersive visual experiences has increased interest in stereoscopic 3D video generation. Despite significant advances in video synthesis, creating 3D videos remains challenging due to the relative scarcity of 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-05-02 Michal Geyer , Omer Tov , Linyi Jin , Richard Tucker , Inbar Mosseri , Tali Dekel , Noah Snavely

The growing adoption of XR devices has fueled strong demand for high-quality stereo video, yet its production remains costly and artifact-prone. To address this challenge, we present StereoWorld, an end-to-end framework that repurposes a…

Computer Vision and Pattern Recognition · Computer Science 2025-12-12 Ke Xing , Xiaojie Jin , Longfei Li , Yuyang Yin , Hanwen Liang , Guixun Luo , Chen Fang , Jue Wang , Konstantinos N. Plataniotis , Yao Zhao , Yunchao Wei

Dynamic novel view synthesis aims to capture the temporal evolution of visual content within videos. Existing methods struggle to distinguishing between motion and structure, particularly in scenarios where camera poses are either unknown…

Computer Vision and Pattern Recognition · Computer Science 2024-01-12 Chaoyang Wang , Peiye Zhuang , Aliaksandr Siarohin , Junli Cao , Guocheng Qian , Hsin-Ying Lee , Sergey Tulyakov

We tackle the problem of monocular-to-stereo video conversion and propose a novel architecture for inpainting and refinement of the warped right view obtained by depth-based reprojection of the input left view. We extend the Stable Video…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Nina Shvetsova , Goutam Bhat , Prune Truong , Hilde Kuehne , Federico Tombari

Video generation models have demonstrated great capabilities of producing impressive monocular videos, however, the generation of 3D stereoscopic video remains under-explored. We propose a pose-free and training-free approach for generating…

Computer Vision and Pattern Recognition · Computer Science 2024-07-02 Peng Dai , Feitong Tan , Qiangeng Xu , David Futschik , Ruofei Du , Sean Fanello , Xiaojuan Qi , Yinda Zhang

Current 4D generation methods have achieved noteworthy efficacy with the aid of advanced diffusion generative models. However, these methods lack multi-view spatial-temporal modeling and encounter challenges in integrating diverse prior…

Computer Vision and Pattern Recognition · Computer Science 2024-10-23 Haiyu Zhang , Xinyuan Chen , Yaohui Wang , Xihui Liu , Yunhong Wang , Yu Qiao

Existing dynamic scene generation methods mostly rely on distilling knowledge from pre-trained 3D generative models, which are typically fine-tuned on synthetic object datasets. As a result, the generated scenes are often object-centric and…

Computer Vision and Pattern Recognition · Computer Science 2024-11-22 Heng Yu , Chaoyang Wang , Peiye Zhuang , Willi Menapace , Aliaksandr Siarohin , Junli Cao , Laszlo A Jeni , Sergey Tulyakov , Hsin-Ying Lee

Multi-view or 4D video generation has emerged as a significant research topic. Nonetheless, recent approaches to 4D generation still struggle with fundamental limitations, as they primarily rely on harnessing multiple video diffusion models…

Computer Vision and Pattern Recognition · Computer Science 2025-12-05 Jangho Park , Taesung Kwon , Jong Chul Ye

In this paper, we propose a novel diffusion-based approach to generate stereo images given a text prompt. Since stereo image datasets with large baselines are scarce, training a diffusion model from scratch is not feasible. Therefore, we…

Computer Vision and Pattern Recognition · Computer Science 2025-07-24 Aakash Garg , Libing Zeng , Andrii Tsarov , Nima Khademi Kalantari

Stereo video conversion aims to transform monocular videos into immersive stereo format. Despite the advancements in novel view synthesis, it still remains two major challenges: i) difficulty of achieving high-fidelity and stable results,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Jiale Zhang , Qianxi Jia , Yang Liu , Wei Zhang , Wei Wei , Xin Tian

We propose DiffuStereo, a novel system using only sparse cameras (8 in this work) for high-quality 3D human reconstruction. At its core is a novel diffusion-based stereo module, which introduces diffusion models, a type of powerful…

Computer Vision and Pattern Recognition · Computer Science 2022-07-21 Ruizhi Shao , Zerong Zheng , Hongwen Zhang , Jingxiang Sun , Yebin Liu

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

The rapid growth of stereoscopic displays, including VR headsets and 3D cinemas, has led to increasing demand for high-quality stereo video content. However, producing 3D videos remains costly and complex, while automatic…

Computer Vision and Pattern Recognition · Computer Science 2025-12-19 Guibao Shen , Yihua Du , Wenhang Ge , Jing He , Chirui Chang , Donghao Zhou , Zhen Yang , Luozhou Wang , Xin Tao , Ying-Cong Chen
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