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Stereo video generation has been gaining increasing attention with recent advancements in video diffusion models. However, most existing methods focus on generating 3D stereoscopic videos from monocular 2D videos. These approaches typically…

Computer Vision and Pattern Recognition · Computer Science 2025-06-09 Xingchang Huang , Ashish Kumar Singh , Florian Dubost , Cristina Nader Vasconcelos , Sakar Khattar , Liang Shi , Christian Theobalt , Cengiz Oztireli , Gurprit Singh

We address the problem of generating videos from unposed internet photos. A handful of input images serve as keyframes, and our model interpolates between them to simulate a path moving between the cameras. Given random images, a model's…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Gene Chou , Kai Zhang , Sai Bi , Hao Tan , Zexiang Xu , Fujun Luan , Bharath Hariharan , Noah Snavely

Recently single-view 3D generation via Gaussian splatting has emerged and developed quickly. They learn 3D Gaussians from 2D RGB images generated from pre-trained multi-view diffusion (MVD) models, and have shown a promising avenue for 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Yiyang Shen , Kun Zhou , He Wang , Yin Yang , Tianjia Shao

In this paper, we explore the existing challenges in 3D artistic scene generation by introducing ART3D, a novel framework that combines diffusion models and 3D Gaussian splatting techniques. Our method effectively bridges the gap between…

Computer Vision and Pattern Recognition · Computer Science 2024-05-20 Pengzhi Li , Chengshuai Tang , Qinxuan Huang , Zhiheng Li

Holistic 3D scene understanding entails estimation of both layout configuration and object geometry in a 3D environment. Recent works have shown advances in 3D scene estimation from various input modalities (e.g., images, 3D scans), by…

Computer Vision and Pattern Recognition · Computer Science 2022-11-28 Yinyu Nie , Angela Dai , Xiaoguang Han , Matthias Nießner

Generating temporally coherent high fidelity video is an important milestone in generative modeling research. We make progress towards this milestone by proposing a diffusion model for video generation that shows very promising initial…

Computer Vision and Pattern Recognition · Computer Science 2022-06-24 Jonathan Ho , Tim Salimans , Alexey Gritsenko , William Chan , Mohammad Norouzi , David J. Fleet

Despite remarkable progress in video generation, maintaining long-term scene consistency upon revisiting previously explored areas remains challenging. Existing solutions rely either on explicitly constructing 3D geometry, which suffers…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Jia Li , Han Yan , Yihang Chen , Siqi Li , Xibin Song , Yifu Wang , Jianfei Cai , Tien-Tsin Wong , Pan Ji

In this paper, we introduce \textbf{DimensionX}, a framework designed to generate photorealistic 3D and 4D scenes from just a single image with video diffusion. Our approach begins with the insight that both the spatial structure of a 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 Wenqiang Sun , Shuo Chen , Fangfu Liu , Zilong Chen , Yueqi Duan , Jun Zhang , Yikai Wang

Automatically generating a complete 3D scene from a text description, a reference image, or both has significant applications in fields like virtual reality and gaming. However, current methods often generate low-quality textures and…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Zhexiao Xiong , Zhang Chen , Zhong Li , Yi Xu , Nathan Jacobs

Designing complex 3D scenes has been a tedious, manual process requiring domain expertise. Emerging text-to-3D generative models show great promise for making this task more intuitive, but existing approaches are limited to object-level…

Computer Vision and Pattern Recognition · Computer Science 2023-03-24 Ryan Po , Gordon Wetzstein

The accurate reconstruction of dynamic street scenes is critical for applications in autonomous driving, augmented reality, and virtual reality. Traditional methods relying on dense point clouds and triangular meshes struggle with moving…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Peizhen Zheng , Dongjing Jiang , Qingchong Jiao , Redouane EL Bouchtaoui , Flynnwell Jianfei Zhang

The increased demand for 3D data in AR/VR, robotics and gaming applications, gave rise to powerful generative pipelines capable of synthesizing high-quality 3D objects. Most of these models rely on the Score Distillation Sampling (SDS)…

Computer Vision and Pattern Recognition · Computer Science 2023-12-12 Ziyu Wan , Despoina Paschalidou , Ian Huang , Hongyu Liu , Bokui Shen , Xiaoyu Xiang , Jing Liao , Leonidas Guibas

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

While image diffusion models have made significant progress in text-driven 3D content creation, they often fail to accurately capture the intended meaning of text prompts, especially for view information. This limitation leads to the Janus…

Computer Vision and Pattern Recognition · Computer Science 2024-03-22 Zhipeng Hu , Minda Zhao , Chaoyi Zhao , Xinyue Liang , Lincheng Li , Zeng Zhao , Changjie Fan , Xiaowei Zhou , Xin Yu

We are living in a flourishing era of digital media, where everyone has the potential to become a personal filmmaker. Current research on video generation suggests a promising avenue for controllable film creation in pixel space using…

Computer Vision and Pattern Recognition · Computer Science 2025-07-03 Weiliang Chen , Fangfu Liu , Diankun Wu , Haowen Sun , Jiwen Lu , Yueqi Duan

The synthesis of immersive 3D scenes from text is rapidly maturing, driven by novel video generative models and feed-forward 3D reconstruction, with vast potential in AR/VR and world modeling. While panoramic images have proven effective…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Felix Wimbauer , Fabian Manhardt , Michael Oechsle , Nikolai Kalischek , Christian Rupprecht , Daniel Cremers , Federico Tombari

Recent advances in 3D generation have improved the fidelity and geometric details of synthesized 3D assets. However, due to the inherent ambiguity of single-view observations and the lack of robust global structural priors caused by limited…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Wenyue Chen , Wenjue Chen , Peng Li , Qinghe Wang , Xu Jia , Heliang Zheng , Rongfei Jia , Yuan Liu , Ronggang Wang

Creating diverse and high-quality 3D assets with an automatic generative model is highly desirable. Despite extensive efforts on 3D generation, most existing works focus on the generation of a single category or a few categories. In this…

Computer Vision and Pattern Recognition · Computer Science 2023-09-18 Ziang Cao , Fangzhou Hong , Tong Wu , Liang Pan , Ziwei Liu

While the generation of 3D content from single-view images has been extensively studied, the creation of physically consistent 3D dynamic scenes from videos remains in its early stages. We propose a novel framework leveraging generative 3D…

Graphics · Computer Science 2025-10-31 Zhiwei Zhao , Alan Zhao , Minchen Li , Yixin Hu

Recent advances in 3D Gaussian Splatting (3DGS) have enabled efficient free-viewpoint rendering and photorealistic scene reconstruction. While on-the-fly extensions of 3DGS have shown promise for real-time reconstruction from monocular RGB…

Computer Vision and Pattern Recognition · Computer Science 2025-12-10 Yijia Guo , Tong Hu , Zhiwei Li , Liwen Hu , Keming Qian , Xitong Lin , Shengbo Chen , Tiejun Huang , Lei Ma
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