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One challenge that remains open in 3D deep learning is how to efficiently represent 3D data to feed deep networks. Recent works have relied on volumetric or point cloud representations, but such approaches suffer from a number of issues…

Computer Vision and Pattern Recognition · Computer Science 2019-01-25 Jhony K. Pontes , Chen Kong , Sridha Sridharan , Simon Lucey , Anders Eriksson , Clinton Fookes

Human Mesh Recovery (HMR) aims to reconstruct 3D human pose and shape from 2D observations and is fundamental to human-centric understanding in real-world scenarios. While recent image-based HMR methods such as SAM 3D Body achieve strong…

Computer Vision and Pattern Recognition · Computer Science 2025-12-10 Mingqi Gao , Yunqi Miao , Jungong Han

We introduce Complet4R, a novel end-to-end framework for Geometric Complete 4D Reconstruction, which aims to recover temporally coherent and geometrically complete reconstruction for dynamic scenes. Our method formalizes the task of…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Weibang Wang , Kenan Li , Zhuoguang Chen , Yijun Yuan , Hang Zhao

Recent advances in deep learning have significantly pushed the state-of-the-art in photorealistic video animation given a single image. In this paper, we extrapolate those advances to the 3D domain, by studying 3D image-to-video translation…

Computer Vision and Pattern Recognition · Computer Science 2020-07-22 Rolandos Alexandros Potamias , Jiali Zheng , Stylianos Ploumpis , Giorgos Bouritsas , Evangelos Ververas , Stefanos Zafeiriou

Many deep learning based 3D face reconstruction methods have been proposed recently, however, few of them have applications in games. Current game character customization systems either require players to manually adjust considerable face…

Computer Vision and Pattern Recognition · Computer Science 2021-02-09 Jiangke Lin , Yi Yuan , Zhengxia Zou

Despite significant progress in 4D content generation, the conversion of monocular videos into high-quality animated 3D assets with explicit 4D meshes remains considerably challenging. The scarcity of large-scale, naturally captured 4D mesh…

Computer Vision and Pattern Recognition · Computer Science 2025-12-12 Kehong Gong , Zhengyu Wen , Mingxi Xu , Weixia He , Qi Wang , Ning Zhang , Zhengyu Li , Chenbin Li , Dongze Lian , Wei Zhao , Xiaoyu He , Mingyuan Zhang

We propose MeshLRM, a novel LRM-based approach that can reconstruct a high-quality mesh from merely four input images in less than one second. Different from previous large reconstruction models (LRMs) that focus on NeRF-based…

Computer Vision and Pattern Recognition · Computer Science 2025-01-24 Xinyue Wei , Kai Zhang , Sai Bi , Hao Tan , Fujun Luan , Valentin Deschaintre , Kalyan Sunkavalli , Hao Su , Zexiang Xu

In this paper, we propose a novel learning approach for feed-forward one-shot 4D head avatar synthesis. Different from existing methods that often learn from reconstructing monocular videos guided by 3DMM, we employ pseudo multi-view videos…

Computer Vision and Pattern Recognition · Computer Science 2024-07-12 Yu Deng , Duomin Wang , Baoyuan Wang

Reconstructing dynamic 4D scenes remains challenging due to the presence of moving objects that corrupt camera pose estimation. Existing optimization methods alleviate this issue with additional supervision, but they are mostly…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Juntong Fang , Zequn Chen , Weiqi Zhang , Donglin Di , Xuancheng Zhang , Chengmin Yang , Yu-Shen Liu

Meshes are the de facto 3D representation in the industry but are labor-intensive to produce. Recently, a line of research has focused on autoregressively generating meshes. This approach processes meshes into a sequence composed of…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Yiwen Chen , Yikai Wang , Yihao Luo , Zhengyi Wang , Zilong Chen , Jun Zhu , Chi Zhang , Guosheng Lin

We present 4DNeX, the first feed-forward framework for generating 4D (i.e., dynamic 3D) scene representations from a single image. In contrast to existing methods that rely on computationally intensive optimization or require multi-frame…

Computer Vision and Pattern Recognition · Computer Science 2025-08-19 Zhaoxi Chen , Tianqi Liu , Long Zhuo , Jiawei Ren , Zeng Tao , He Zhu , Fangzhou Hong , Liang Pan , Ziwei Liu

Understanding and predicting dynamics of the physical world can enhance a robot's ability to plan and interact effectively in complex environments. While recent video generation models have shown strong potential in modeling dynamic scenes,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Zeyi Liu , Shuang Li , Eric Cousineau , Siyuan Feng , Benjamin Burchfiel , Shuran Song

We introduce Mono4DGS-HDR, the first system for reconstructing renderable 4D high dynamic range (HDR) scenes from unposed monocular low dynamic range (LDR) videos captured with alternating exposures. To tackle such a challenging problem, we…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Jinfeng Liu , Lingtong Kong , Mi Zhou , Jinwen Chen , Dan Xu

We propose Dyn-HaMR, to the best of our knowledge, the first approach to reconstruct 4D global hand motion from monocular videos recorded by dynamic cameras in the wild. Reconstructing accurate 3D hand meshes from monocular videos is a…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Zhengdi Yu , Stefanos Zafeiriou , Tolga Birdal

In this paper, we address the problem of 3D object mesh reconstruction from RGB videos. Our approach combines the best of multi-view geometric and data-driven methods for 3D reconstruction by optimizing object meshes for multi-view…

Computer Vision and Pattern Recognition · Computer Science 2019-03-21 Chen-Hsuan Lin , Oliver Wang , Bryan C. Russell , Eli Shechtman , Vladimir G. Kim , Matthew Fisher , Simon Lucey

Monocular image-based 3D reconstruction of faces is a long-standing problem in computer vision. Since image data is a 2D projection of a 3D face, the resulting depth ambiguity makes the problem ill-posed. Most existing methods rely on…

Computer Vision and Pattern Recognition · Computer Science 2019-04-10 Ayush Tewari , Florian Bernard , Pablo Garrido , Gaurav Bharaj , Mohamed Elgharib , Hans-Peter Seidel , Patrick Pérez , Michael Zollhöfer , Christian Theobalt

Generating animated 3D objects is at the heart of many applications, yet most advanced works are typically difficult to apply in practice because of their limited setup, their long runtime, or their limited quality. We introduce ActionMesh,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-02 Remy Sabathier , David Novotny , Niloy J. Mitra , Tom Monnier

Camera redirection aims to replay a dynamic scene from a single monocular video under a user-specified camera trajectory. However, large-angle redirection is inherently ill-posed: a monocular video captures only a narrow spatio-temporal…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Wei Cao , Hao Zhang , Fengrui Tian , Yulun Wu , Yingying Li , Shenlong Wang , Ning Yu , Yaoyao Liu

DreamFusion established a new paradigm for unsupervised 3D reconstruction from virtual views by combining advances in generative models and differentiable rendering. However, the underlying multi-view rendering, along with supervision from…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Ananta R. Bhattarai , Xingzhe He , Alla Sheffer , Helge Rhodin

3D Human Body Reconstruction from a monocular image is an important problem in computer vision with applications in virtual and augmented reality platforms, animation industry, en-commerce domain, etc. While several of the existing works…

Computer Vision and Pattern Recognition · Computer Science 2019-08-20 Abbhinav Venkat , Chaitanya Patel , Yudhik Agrawal , Avinash Sharma
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