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Related papers: Helix4D: Complex 4D Mesh Generation

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We present a dynamic reconstruction system that receives a casual monocular RGB video as input, and outputs a complete and persistent reconstruction of the scene. In other words, we reconstruct not only the the currently visible parts of…

Computer Vision and Pattern Recognition · Computer Science 2025-12-19 Kirill Mazur , Marwan Taher , Andrew J. Davison

Recent advances in diffusion models have revolutionized 2D and 3D content creation, yet generating photorealistic dynamic 4D scenes remains a significant challenge. Existing dynamic 4D generation methods typically rely on distilling…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Vinayak Gupta , Yunze Man , Yu-Xiong Wang

In this article, we provide a detailed survey of techniques for hexahedral mesh generation. We cover the whole spectrum of alternative approaches to mesh generation, as well as post processing algorithms for connectivity editing and mesh…

Generative artificial intelligence has recently progressed from static image and video synthesis to 3D content generation, culminating in the emergence of 4D generation-the task of synthesizing temporally coherent dynamic 3D assets guided…

Computer Vision and Pattern Recognition · Computer Science 2025-07-25 Qiaowei Miao , Kehan Li , Jinsheng Quan , Zhiyuan Min , Shaojie Ma , Yichao Xu , Yi Yang , Ping Liu , Yawei Luo

We propose the first framework capable of computing a 4D spatio-temporal grid of video frames and 3D Gaussian particles for each time step using a feed-forward architecture. Our architecture has two main components, a 4D video model and a…

The field of 4D point cloud understanding is rapidly developing with the goal of analyzing dynamic 3D point cloud sequences. However, it remains a challenging task due to the sparsity and lack of texture in point clouds. Moreover, the…

Computer Vision and Pattern Recognition · Computer Science 2023-12-13 Linglin Jing , Ying Xue , Xu Yan , Chaoda Zheng , Dong Wang , Ruimao Zhang , Zhigang Wang , Hui Fang , Bin Zhao , Zhen Li

We study the problem of shape generation in 3D mesh representation from a small number of color images with or without camera poses. While many previous works learn to hallucinate the shape directly from priors, we adopt to further improve…

Computer Vision and Pattern Recognition · Computer Science 2022-04-22 Chao Wen , Yinda Zhang , Chenjie Cao , Zhuwen Li , Xiangyang Xue , Yanwei Fu

In this work, we introduce Unique3D, a novel image-to-3D framework for efficiently generating high-quality 3D meshes from single-view images, featuring state-of-the-art generation fidelity and strong generalizability. Previous methods based…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Kailu Wu , Fangfu Liu , Zhihan Cai , Runjie Yan , Hanyang Wang , Yating Hu , Yueqi Duan , Kaisheng Ma

My research focuses on the analysis, recovery, and generation of 4D content, where 4D includes three spatial dimensions (x, y, z) and a temporal dimension t, such as shape and motion. This focus goes beyond static objects to include dynamic…

Computer Vision and Pattern Recognition · Computer Science 2024-09-24 Zhiyang Dou

Mesh is a fundamental representation of 3D assets in various industrial applications, and is widely supported by professional softwares. However, due to its irregular structure, mesh creation and manipulation is often time-consuming and…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Zhaoyang Lyu , Ben Fei , Jinyi Wang , Xudong Xu , Ya Zhang , Weidong Yang , Bo Dai

Current generative models struggle to synthesize dynamic 4D driving scenes that simultaneously support temporal extrapolation and spatial novel view synthesis (NVS) without per-scene optimization. Bridging generation and novel view…

Computer Vision and Pattern Recognition · Computer Science 2025-09-25 Hao Lu , Zhuang Ma , Guangfeng Jiang , Wenhang Ge , Bohan Li , Yuzhan Cai , Wenzhao Zheng , Yunpeng Zhang , Yingcong Chen

Current 4D generation methods have achieved noteworthy efficacy with the aid of advanced diffusion generative models. However, these methods lack multi-view spatial-temporal modeling and encounter challenges in integrating diverse prior…

Computer Vision and Pattern Recognition · Computer Science 2024-10-23 Haiyu Zhang , Xinyuan Chen , Yaohui Wang , Xihui Liu , Yunhong Wang , Yu Qiao

Dynamic spatial reasoning from monocular video is essential for bridging visual intelligence and the physical world, yet remains challenging for vision-language models (VLMs). Prior approaches either verbalize spatial-temporal reasoning…

Computer Vision and Pattern Recognition · Computer Science 2026-05-25 Zhangquan Chen , Manyuan Zhang , Xinlei Yu , Xiang An , Bo Li , Xin Xie , ZiDong Wang , Mingze Sun , Shuang Chen , Hongyu Li , Xiaobin Hu , Ruqi Huang

Recent progress in image and video synthesis has inspired their use in advancing 3D scene generation. However, we observe that text-to-image and -video approaches struggle to maintain scene- and object-level consistency beyond a limited…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Manuel-Andreas Schneider , Angela Dai

Recently, the generation of dynamic 3D objects from a video has shown impressive results. Existing methods directly optimize Gaussians using whole information in frames. However, when dynamic regions are interwoven with static regions…

Computer Vision and Pattern Recognition · Computer Science 2025-06-30 Liying Yang , Chen Liu , Zhenwei Zhu , Ajian Liu , Hui Ma , Jian Nong , Yanyan Liang

Despite advances in Multimodal LLMs (MLLMs), their ability to reason over 3D structures and temporal dynamics remains limited, constrained by weak 4D perception and temporal understanding. Existing 3D and 4D Video Question Answering (VQA)…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Chiao-An Yang , Ryo Hachiuma , Sifei Liu , Subhashree Radhakrishnan , Raymond A. Yeh , Yu-Chiang Frank Wang , Min-Hung Chen

Generating high-quality 4D content from monocular videos for applications such as digital humans and AR/VR poses challenges in ensuring temporal and spatial consistency, preserving intricate details, and incorporating user guidance…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Minghao Yin , Yukang Cao , Songyou Peng , Kai Han

We propose a framework to learn a structured latent space to represent 4D human body motion, where each latent vector encodes a full motion of the whole 3D human shape. On one hand several data-driven skeletal animation models exist…

Computer Vision and Pattern Recognition · Computer Science 2022-09-02 Mathieu Marsot , Stefanie Wuhrer , Jean-Sebastien Franco , Stephane Durocher

World models have made significant progress in modeling dynamic environments; however, most embodied world models are still restricted to 2D representations, lacking the comprehensive multi-view information essential for embodied spatial…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Peiyan Tu , Hanxin Zhu , Jingwen Sun , Shaojie Ren , Cong Wang , Jiayi Luo , Xiaoqian Cheng , Zhibo Chen

Recovering a dense 3D body mesh from monocular video remains challenging under occlusion from draping and continuously moving camera viewpoints. This configuration arises in surgical augmented reality (AR), where an anesthetized patient…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Mingxiao Tu , Hoijoon Jung , Alireza Moghadam , Andre Kyme , Jinman Kim
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