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Related papers: Helix4D: Complex 4D Mesh Generation

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Recent advances in diffusion-based generative models have established a new paradigm for image and video relighting. However, extending these capabilities to 4D relighting remains challenging, due primarily to the scarcity of paired 4D…

Computer Vision and Pattern Recognition · Computer Science 2026-02-13 Zhenghuang Wu , Kang Chen , Zeyu Zhang , Hao Tang

Despite the latest remarkable advances in generative modeling, efficient generation of high-quality 3D assets from textual prompts remains a difficult task. A key challenge lies in data scarcity: the most extensive 3D datasets encompass…

Computer Vision and Pattern Recognition · Computer Science 2024-01-17 Antoine Mercier , Ramin Nakhli , Mahesh Reddy , Rajeev Yasarla , Hong Cai , Fatih Porikli , Guillaume Berger

Time series imputation benefits from leveraging cross-feature correlations, yet existing attention-based methods re-discover feature relationships at each layer, lacking persistent anchors to maintain consistent representations. To address…

Machine Learning · Computer Science 2026-05-05 Fengming Zhang , Wenjie Du , Huan Zhang , Ke Yu , Shen Qu

Modeling and rendering of dynamic scenes is challenging, as natural scenes often contain complex phenomena such as thin structures, evolving topology, translucency, scattering, occlusion, and biological motion. Mesh-based reconstruction and…

Graphics · Computer Science 2019-08-14 Stephen Lombardi , Tomas Simon , Jason Saragih , Gabriel Schwartz , Andreas Lehrmann , Yaser Sheikh

We study the problem of synthesizing a long-term dynamic video from only a single image. This is challenging since it requires consistent visual content movements given large camera motions. Existing methods either hallucinate inconsistent…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Liao Shen , Xingyi Li , Huiqiang Sun , Juewen Peng , Ke Xian , Zhiguo Cao , Guosheng Lin

Vision-language models (VLMs) have demonstrated strong performance in 2D scene understanding and generation, but extending this unification to the physical world remains an open challenge. Existing 3D and 4D approaches typically embed scene…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Hanyu Zhou , Gim Hee Lee

Modeling and re-rendering dynamic 3D scenes is a challenging task in 3D vision. Prior approaches build on NeRF and rely on implicit representations. This is slow since it requires many MLP evaluations, constraining real-world applications.…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Ang Cao , Justin Johnson

With the popularity of monocular videos generated by video sharing and live broadcasting applications, reconstructing and editing dynamic scenes in stationary monocular cameras has become a special but anticipated technology. In contrast to…

Computer Vision and Pattern Recognition · Computer Science 2024-02-02 Weixing Xie , Xiao Dong , Yong Yang , Qiqin Lin , Jingze Chen , Junfeng Yao , Xiaohu Guo

We present a video generation model that accurately reproduces object motion, changes in camera viewpoint, and new content that arises over time. Existing video generation methods often fail to produce new content as a function of time…

Computer Vision and Pattern Recognition · Computer Science 2022-06-10 Tim Brooks , Janne Hellsten , Miika Aittala , Ting-Chun Wang , Timo Aila , Jaakko Lehtinen , Ming-Yu Liu , Alexei A. Efros , Tero Karras

In recent years, the increasing demand for dynamic 3D assets in design and gaming applications has given rise to powerful generative pipelines capable of synthesizing high-quality 4D objects. Previous methods generally rely on score…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Qi Sun , Zhiyang Guo , Ziyu Wan , Jing Nathan Yan , Shengming Yin , Wengang Zhou , Jing Liao , Houqiang Li

Given the high complexity of directly generating high-dimensional data such as 4D, we present 4DVD, a cascaded video diffusion model that generates 4D content in a decoupled manner. Unlike previous multi-view video methods that directly…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Shuzhou Yang , Xiaodong Cun , Xiaoyu Li , Yaowei Li , Jian Zhang

Automatically generating high-quality real world 3D scenes is of enormous interest for applications such as virtual reality and robotics simulation. Towards this goal, we introduce NeuralField-LDM, a generative model capable of synthesizing…

Computer Vision and Pattern Recognition · Computer Science 2023-04-20 Seung Wook Kim , Bradley Brown , Kangxue Yin , Karsten Kreis , Katja Schwarz , Daiqing Li , Robin Rombach , Antonio Torralba , Sanja Fidler

Recent advancements in generative models have ignited substantial interest in dynamic 3D content creation (\ie, 4D generation). Existing approaches primarily rely on Score Distillation Sampling (SDS) to infer novel-view videos, typically…

Computer Vision and Pattern Recognition · Computer Science 2025-01-06 Hanxin Zhu , Tianyu He , Xiqian Yu , Junliang Guo , Zhibo Chen , Jiang Bian

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

To generate accurate videos, algorithms have to understand the spatial and temporal dependencies in the world. Current algorithms enable accurate predictions over short horizons but tend to suffer from temporal inconsistencies. When…

Computer Vision and Pattern Recognition · Computer Science 2023-06-02 Wilson Yan , Danijar Hafner , Stephen James , Pieter Abbeel

3D Gaussian Splatting (3DGS) has emerged as an efficient and high-fidelity paradigm for novel view synthesis. To adapt 3DGS for dynamic content, deformable 3DGS incorporates temporally deformable primitives with learnable latent embeddings…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Mufan Liu , Qi Yang , He Huang , Wenjie Huang , Zhenlong Yuan , Zhu Li , Yiling Xu

Recent breakthroughs in 3D generative modeling have yielded remarkable progress in static shape synthesis, yet high-fidelity dynamic 4D generation remains elusive, hindered by temporal artifacts and prohibitive computational demand. We…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Minghao Yin , Wenbo Hu , Jiale Xu , Ying Shan , Kai Han

Recent advances in 4D Gaussian Splatting (4DGS) have extended the high-speed rendering capability of 3D Gaussian Splatting (3DGS) into the temporal domain, enabling real-time rendering of dynamic scenes. However, one of the major remaining…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Sangwoon Kwak , Weeyoung Kwon , Jun Young Jeong , Geonho Kim , Won-Sik Cheong , Jihyong Oh

Recovering 4D from monocular video, which jointly estimates dynamic geometry and camera poses, is an inevitably challenging problem. While recent pointmap-based 3D reconstruction methods (e.g., DUSt3R) have made great progress in…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Shizun Wang , Zhenxiang Jiang , Xingyi Yang , Xinchao Wang

Recent advances in sparse voxel representations have significantly improved the quality of 3D content generation, enabling high-resolution modeling with fine-grained geometry. However, existing frameworks suffer from severe computational…

Computer Vision and Pattern Recognition · Computer Science 2025-08-01 Yiwen Chen , Zhihao Li , Yikai Wang , Hu Zhang , Qin Li , Chi Zhang , Guosheng Lin
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