English
Related papers

Related papers: SV4D: Dynamic 3D Content Generation with Multi-Fra…

200 papers

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

Recent progress in pre-trained diffusion models and 3D generation have spurred interest in 4D content creation. However, achieving high-fidelity 4D generation with spatial-temporal consistency remains a challenge. In this work, we propose…

Computer Vision and Pattern Recognition · Computer Science 2024-03-25 Yifei Zeng , Yanqin Jiang , Siyu Zhu , Yuanxun Lu , Youtian Lin , Hao Zhu , Weiming Hu , Xun Cao , Yao Yao

Recent advances in 2D/3D generative models enable the generation of dynamic 3D objects from a single-view video. Existing approaches utilize score distillation sampling to form the dynamic scene as dynamic NeRF or dense 3D Gaussians.…

Computer Vision and Pattern Recognition · Computer Science 2024-08-15 Zijie Wu , Chaohui Yu , Yanqin Jiang , Chenjie Cao , Fan Wang , Xiang Bai

We present CAT4D, a method for creating 4D (dynamic 3D) scenes from monocular video. CAT4D leverages a multi-view video diffusion model trained on a diverse combination of datasets to enable novel view synthesis at any specified camera…

Computer Vision and Pattern Recognition · Computer Science 2024-12-20 Rundi Wu , Ruiqi Gao , Ben Poole , Alex Trevithick , Changxi Zheng , Jonathan T. Barron , Aleksander Holynski

Recent breakthroughs in video generation, powered by large-scale datasets and diffusion techniques, have shown that video diffusion models can function as implicit 4D novel view synthesizers. Nevertheless, current methods primarily…

Computer Vision and Pattern Recognition · Computer Science 2025-10-09 Yihao Zhi , Chenghong Li , Hongjie Liao , Xihe Yang , Zhengwentai Sun , Jiahao Chang , Xiaodong Cun , Wensen Feng , Xiaoguang Han

Generating 4D scenes from a single-view video is inherently ill-posed: a single viewpoint lacks the information needed to recover a complete, dynamic scene with full coverage. Existing methods are typically limited to monocular videos,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Tingxi Chen , Ke Hao , Yabo Chen , Zhengxue Cheng , Rong Xie , Li Song , Haibin Huang , Chi Zhang , Xuelong Li

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

Synthesizing novel views from monocular videos of dynamic scenes remains a challenging problem. Scene-specific methods that optimize 4D representations with explicit motion priors often break down in highly dynamic regions where multi-view…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Thomas Tanay , Mohammed Brahimi , Michal Nazarczuk , Qingwen Zhang , Sibi Catley-Chandar , Arthur Moreau , Zhensong Zhang , Eduardo Pérez-Pellitero

We propose 4Real-Video, a novel framework for generating 4D videos, organized as a grid of video frames with both time and viewpoint axes. In this grid, each row contains frames sharing the same timestep, while each column contains frames…

Computer Vision and Pattern Recognition · Computer Science 2024-12-06 Chaoyang Wang , Peiye Zhuang , Tuan Duc Ngo , Willi Menapace , Aliaksandr Siarohin , Michael Vasilkovsky , Ivan Skorokhodov , Sergey Tulyakov , Peter Wonka , Hsin-Ying Lee

With the rapid advancements in diffusion models and 3D generation techniques, dynamic 3D content generation has become a crucial research area. However, achieving high-fidelity 4D (dynamic 3D) generation with strong spatial-temporal…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Jinwei Li , Huan-ang Gao , Wenyi Li , Haohan Chi , Chenyu Liu , Chenxi Du , Yiqian Liu , Mingju Gao , Guiyu Zhang , Zongzheng Zhang , Li Yi , Yao Yao , Jingwei Zhao , Hongyang Li , Yikai Wang , Hao Zhao

Live-streaming Novel View Synthesis (NVS) from unposed multi-view video remains an open challenge in a wide range of applications. Existing methods for dynamic scene representation typically require ground-truth camera parameters and…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Pedro Quesado , Erkut Akdag , Yasaman Kashefbahrami , Willem Menu , Egor Bondarev

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

We introduce Diff4Splat, a feed-forward method that synthesizes controllable and explicit 4D scenes from a single image. Our approach unifies the generative priors of video diffusion models with geometry and motion constraints learned from…

Computer Vision and Pattern Recognition · Computer Science 2026-04-08 Panwang Pan , Chenguo Lin , Jingjing Zhao , Chenxin Li , Yuchen Lin , Haopeng Li , Honglei Yan , Kairun Wen , Yunlong Lin , Yixuan Yuan , Yadong Mu

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

Modern video generative models based on diffusion models can produce very realistic clips, but they are computationally inefficient, often requiring minutes of GPU time for just a few seconds of video. This inefficiency poses a critical…

Computer Vision and Pattern Recognition · Computer Science 2026-01-15 Jieying Chen , Jeffrey Hu , Joan Lasenby , Ayush Tewari

In this paper, we present MVTokenFlow for high-quality 4D content creation from monocular videos. Recent advancements in generative models such as video diffusion models and multiview diffusion models enable us to create videos or 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-02-18 Hanzhuo Huang , Yuan Liu , Ge Zheng , Jiepeng Wang , Zhiyang Dou , Sibei Yang

Recent advances in 4D generation mainly focus on generating 4D content by distilling pre-trained text or single-view image-conditioned models. It is inconvenient for them to take advantage of various off-the-shelf 3D assets with multi-view…

Computer Vision and Pattern Recognition · Computer Science 2024-09-10 Yanqin Jiang , Chaohui Yu , Chenjie Cao , Fan Wang , Weiming Hu , Jin Gao

Despite recent advancements in neural 3D reconstruction, the dependence on dense multi-view captures restricts their broader applicability. In this work, we propose \textbf{ViewCrafter}, a novel method for synthesizing high-fidelity novel…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Wangbo Yu , Jinbo Xing , Li Yuan , Wenbo Hu , Xiaoyu Li , Zhipeng Huang , Xiangjun Gao , Tien-Tsin Wong , Ying Shan , Yonghong Tian

With the increasing popularity of autonomous driving based on the powerful and unified bird's-eye-view (BEV) representation, a demand for high-quality and large-scale multi-view video data with accurate annotation is urgently required.…

Computer Vision and Pattern Recognition · Computer Science 2023-10-13 Xiaofan Li , Yifu Zhang , Xiaoqing Ye

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