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We present Stable Video 3D (SV3D) -- a latent video diffusion model for high-resolution, image-to-multi-view generation of orbital videos around a 3D object. Recent work on 3D generation propose techniques to adapt 2D generative models for…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Vikram Voleti , Chun-Han Yao , Mark Boss , Adam Letts , David Pankratz , Dmitry Tochilkin , Christian Laforte , Robin Rombach , Varun Jampani

We present Stable Video 4D (SV4D), a latent video diffusion model for multi-frame and multi-view consistent dynamic 3D content generation. Unlike previous methods that rely on separately trained generative models for video generation and…

Computer Vision and Pattern Recognition · Computer Science 2025-03-03 Yiming Xie , Chun-Han Yao , Vikram Voleti , Huaizu Jiang , Varun Jampani

We present Stable Virtual Camera (Seva), a generalist diffusion model that creates novel views of a scene, given any number of input views and target cameras. Existing works struggle to generate either large viewpoint changes or temporally…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Jensen Zhou , Hang Gao , Vikram Voleti , Aaryaman Vasishta , Chun-Han Yao , Mark Boss , Philip Torr , Christian Rupprecht , Varun Jampani

We present Stable Video 4D 2.0 (SV4D 2.0), a multi-view video diffusion model for dynamic 3D asset generation. Compared to its predecessor SV4D, SV4D 2.0 is more robust to occlusions and large motion, generalizes better to real-world…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Chun-Han Yao , Yiming Xie , Vikram Voleti , Huaizu Jiang , Varun Jampani

Diffusion-based methods can generate realistic images and videos, but they struggle to edit existing objects in a video while preserving their appearance over time. This prevents diffusion models from being applied to natural video editing…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Wenhao Chai , Xun Guo , Gaoang Wang , Yan Lu

Diffusion-based video generation models have demonstrated remarkable success in obtaining high-fidelity videos through the iterative denoising process. However, these models require multiple denoising steps during sampling, resulting in…

Computer Vision and Pattern Recognition · Computer Science 2024-10-28 Zhixing Zhang , Yanyu Li , Yushu Wu , Yanwu Xu , Anil Kag , Ivan Skorokhodov , Willi Menapace , Aliaksandr Siarohin , Junli Cao , Dimitris Metaxas , Sergey Tulyakov , Jian Ren

We present Stable Video Diffusion - a latent video diffusion model for high-resolution, state-of-the-art text-to-video and image-to-video generation. Recently, latent diffusion models trained for 2D image synthesis have been turned into…

Computer Vision and Pattern Recognition · Computer Science 2023-11-28 Andreas Blattmann , Tim Dockhorn , Sumith Kulal , Daniel Mendelevitch , Maciej Kilian , Dominik Lorenz , Yam Levi , Zion English , Vikram Voleti , Adam Letts , Varun Jampani , Robin Rombach

We present Stable View Synthesis (SVS). Given a set of source images depicting a scene from freely distributed viewpoints, SVS synthesizes new views of the scene. The method operates on a geometric scaffold computed via…

Computer Vision and Pattern Recognition · Computer Science 2021-05-04 Gernot Riegler , Vladlen Koltun

Recent advancements in diffusion models have set new benchmarks in image and video generation, enabling realistic visual synthesis across single- and multi-frame contexts. However, these models still struggle with efficiently and explicitly…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Qihang Zhang , Shuangfei Zhai , Miguel Angel Bautista , Kevin Miao , Alexander Toshev , Joshua Susskind , Jiatao Gu

Although powerful for image generation, consistent and controllable video is a longstanding problem for diffusion models. Video models require extensive training and computational resources, leading to high costs and large environmental…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Muhammad Haaris Khan , Hadrien Reynaud , Bernhard Kainz

Diffusion models, such as Stable Diffusion, have shown incredible performance on text-to-image generation. Since text-to-image generation often requires models to generate visual concepts with fine-grained details and attributes specified…

Computer Vision and Pattern Recognition · Computer Science 2024-04-26 Xuehai He , Weixi Feng , Tsu-Jui Fu , Varun Jampani , Arjun Akula , Pradyumna Narayana , Sugato Basu , William Yang Wang , Xin Eric Wang

Generative models have increasingly impacted various tasks, from computer vision to interior design and beyond. Stable Diffusion, a powerful diffusion model, enables the creation of high-resolution images with intricate details from text…

Computer Vision and Pattern Recognition · Computer Science 2025-02-25 Boyang Deng

Recent advances in diffusion models have set an impressive milestone in many generation tasks, and trending works such as DALL-E2, Imagen, and Stable Diffusion have attracted great interest. Despite the rapid landscape changes, recent new…

Computer Vision and Pattern Recognition · Computer Science 2024-01-15 Xingqian Xu , Zhangyang Wang , Eric Zhang , Kai Wang , Humphrey Shi

Research on video generation has recently made tremendous progress, enabling high-quality videos to be generated from text prompts or images. Adding control to the video generation process is an important goal moving forward and recent…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Zhengfei Kuang , Shengqu Cai , Hao He , Yinghao Xu , Hongsheng Li , Leonidas Guibas , Gordon Wetzstein

The ability to visualize a structure from multiple perspectives is crucial for comprehensive planning and presentation. This paper introduces an advanced application of generative models, akin to Stable Video Diffusion, tailored for…

Human-Computer Interaction · Computer Science 2024-06-05 Mingming Wang , Elijah Miller

We present Stable Video Materials 3D (SViM3D), a framework to predict multi-view consistent physically based rendering (PBR) materials, given a single image. Recently, video diffusion models have been successfully used to reconstruct 3D…

Graphics · Computer Science 2025-11-04 Andreas Engelhardt , Mark Boss , Vikram Voleti , Chun-Han Yao , Hendrik P. A. Lensch , Varun Jampani

Background: Text-to-image generation models are widely used across numerous domains. Among these models, Stable Diffusion (SD) - an open-source text-to-image generation model - has become the most popular, producing over 12 billion images…

Software Engineering · Computer Science 2025-12-08 Giordano d'Aloisio , Tosin Fadahunsi , Jay Choy , Rebecca Moussa , Federica Sarro

We present BetterScene, an approach to enhance novel view synthesis (NVS) quality for diverse real-world scenes using extremely sparse, unconstrained photos. BetterScene leverages the production-ready Stable Video Diffusion (SVD) model…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Yuci Han , Charles Toth , John E. Anderson , William J. Shuart , Alper Yilmaz

Generating novel views of an object from a single image is a challenging task. It requires an understanding of the underlying 3D structure of the object from an image and rendering high-quality, spatially consistent new views. While recent…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Jeong-gi Kwak , Erqun Dong , Yuhe Jin , Hanseok Ko , Shweta Mahajan , Kwang Moo Yi

Stable Diffusion Models (SDMs) have shown remarkable proficiency in image synthesis. However, their broad application is impeded by their large model sizes and intensive computational requirements, which typically require expensive cloud…

Computer Vision and Pattern Recognition · Computer Science 2024-10-31 Chenqian Yan , Songwei Liu , Hongjian Liu , Xurui Peng , Xiaojian Wang , Fangmin Chen , Lean Fu , Xing Mei
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