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Related papers: DragMesh: Interactive 3D Generation Made Easy

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Recent advances in 4D content generation have attracted increasing attention, yet creating high-quality animated 3D models remains challenging due to the complexity of modeling spatio-temporal distributions and the scarcity of 4D training…

Computer Vision and Pattern Recognition · Computer Science 2025-06-12 Zijie Wu , Chaohui Yu , Fan Wang , Xiang Bai

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

Rigged 3D assets are fundamental to 3D deformation and animation. However, existing 3D generation methods face challenges in generating animatable geometry, while rigging techniques lack fine-grained structural control over skeleton…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Ruisi Zhao , Haoren Zheng , Zongxin Yang , Hehe Fan , Yi Yang

Video-guided 3D animation holds immense potential for content creation, offering intuitive and precise control over dynamic assets. However, practical deployment faces a critical yet frequently overlooked hurdle: the pose misalignment…

Computer Vision and Pattern Recognition · Computer Science 2026-05-15 Zijie Wu , Lixin Xu , Puhua Jiang , Sicong Liu , Chunchao Guo , Xiang Bai

We introduce Drag4D, an interactive framework that integrates object motion control within text-driven 3D scene generation. This framework enables users to define 3D trajectories for the 3D objects generated from a single image, seamlessly…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Minjun Kang , Inkyu Shin , Taeyeop Lee , In So Kweon , Kuk-Jin Yoon

We address the challenge of generating 3D articulated objects in a controllable fashion. Currently, modeling articulated 3D objects is either achieved through laborious manual authoring, or using methods from prior work that are hard to…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Jiayi Liu , Hou In Ivan Tam , Ali Mahdavi-Amiri , Manolis Savva

Understanding the motion of articulated mechanical assemblies from static geometry remains a core challenge in 3D perception and design automation. Prior work on everyday articulated objects such as doors and laptops typically assumes…

Computer Vision and Pattern Recognition · Computer Science 2025-09-17 Mayank Patel , Rahul Jain , Asim Unmesh , Karthik Ramani

Recent advances in 4D content generation have attracted increasing attention, yet creating high-quality animated 3D models remains challenging due to the complexity of modeling spatio-temporal distributions and the scarcity of 4D training…

Computer Vision and Pattern Recognition · Computer Science 2026-04-30 Zijie Wu , Chaohui Yu , Fan Wang , Xiang Bai

Single-image 3D generation has emerged as a prominent research topic, playing a vital role in virtual reality, 3D modeling, and digital content creation. However, existing methods face challenges such as a lack of multi-view geometric…

Computer Vision and Pattern Recognition · Computer Science 2025-02-25 Jinbo Yan , Alan Zhao , Yixin Hu

Human motion generation is a significant pursuit in generative computer vision with widespread applications in film-making, video games, AR/VR, and human-robot interaction. Current methods mainly utilize either diffusion-based generative…

Computer Vision and Pattern Recognition · Computer Science 2025-02-03 Canxuan Gang

3D Human motion generation is pivotal across film, animation, gaming, and embodied intelligence. Traditional 3D motion synthesis relies on costly motion capture, while recent work shows that 2D videos provide rich, temporally coherent…

Graphics · Computer Science 2026-05-20 Yi-Yang Zhang , Tengjiao Sun , Pengcheng Fang , Deng-Bao Wang , Xiaohao Cai , Min-Ling Zhang , Hansung Kim

Recent advances in 3D vision have led to specialized models for either 3D understanding (e.g., shape classification, segmentation, reconstruction) or 3D generation (e.g., synthesis, completion, and editing). However, these tasks are often…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Peng Huang , Yifeng Chen , Zeyu Zhang , Hao Tang

Creating 3D textured meshes using generative artificial intelligence has garnered significant attention recently. While existing methods support text-based generative texture generation or editing on 3D meshes, they often struggle to…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Yudi Zhang , Qi Xu , Lei Zhang

Lightweight, controllable, and physically plausible human motion synthesis is crucial for animation, virtual reality, robotics, and human-computer interaction applications. Existing methods often compromise between computational efficiency,…

Computer Vision and Pattern Recognition · Computer Science 2025-01-29 Arvin Tashakori , Arash Tashakori , Gongbo Yang , Z. Jane Wang , Peyman Servati

3D articulated objects modeling has long been a challenging problem, since it requires to capture both accurate surface geometries and semantically meaningful and spatially precise structures, parts, and joints. Existing methods heavily…

Computer Vision and Pattern Recognition · Computer Science 2025-05-13 Xiaowen Qiu , Jincheng Yang , Yian Wang , Zhehuan Chen , Yufei Wang , Tsun-Hsuan Wang , Zhou Xian , Chuang Gan

We propose DriveAnyMesh, a method for driving mesh guided by monocular video. Current 4D generation techniques encounter challenges with modern rendering engines. Implicit methods have low rendering efficiency and are unfriendly to…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Yahao Shi , Yang Liu , Yanmin Wu , Xing Liu , Chen Zhao , Jie Luo , Bin Zhou

Drag-based editing has become popular in 2D content creation, driven by the capabilities of image generative models. However, extending this technique to 3D remains a challenge. Existing 3D drag-based editing methods, whether employing…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Honghua Chen , Yushi Lan , Yongwei Chen , Yifan Zhou , Xingang Pan

The creation of plausible and controllable 3D human motion animations is a long-standing problem that requires a manual intervention of skilled artists. Current machine learning approaches can semi-automate the process, however, they are…

Computer Vision and Pattern Recognition · Computer Science 2021-11-29 Kacper Kania , Marek Kowalski , Tomasz Trzciński

In recent years, diffusion models have achieved tremendous success in the field of video generation, with controllable video generation receiving significant attention. However, existing control methods still face two limitations: Firstly,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Zhang Wan , Sheng Tang , Jiawei Wei , Ruize Zhang , Juan Cao

Articulated 3D object generation is fundamental for creating realistic, functional, and interactable virtual assets which are not simply static. We introduce MeshArt, a hierarchical transformer-based approach to generate articulated 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Daoyi Gao , Yawar Siddiqui , Lei Li , Angela Dai
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