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Related papers: InstantMesh: Efficient 3D Mesh Generation from a S…

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Text-to-3D with diffusion models has achieved remarkable progress in recent years. However, existing methods either rely on score distillation-based optimization which suffer from slow inference, low diversity and Janus problems, or are…

Computer Vision and Pattern Recognition · Computer Science 2023-11-27 Jiahao Li , Hao Tan , Kai Zhang , Zexiang Xu , Fujun Luan , Yinghao Xu , Yicong Hong , Kalyan Sunkavalli , Greg Shakhnarovich , Sai Bi

Automatic 3D content creation seeks to replace labor-intensive modeling and scanning pipelines with systems that can synthesize or recover 3D assets directly from text or images. Its applications span video games, virtual reality, robotics,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Jiahao Li

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

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

Text-to-3D generation has attracted much attention from the computer vision community. Existing methods mainly optimize a neural field from scratch for each text prompt, relying on heavy and repetitive training cost which impedes their…

Computer Vision and Pattern Recognition · Computer Science 2024-04-30 Ming Li , Pan Zhou , Jia-Wei Liu , Jussi Keppo , Min Lin , Shuicheng Yan , Xiangyu Xu

Recent mesh generation approaches typically tokenize triangle meshes into sequences of tokens and train autoregressive models to generate these tokens sequentially. Despite substantial progress, such token sequences inevitably reuse…

Computer Vision and Pattern Recognition · Computer Science 2026-01-16 Jeonghwan Kim , Yushi Lan , Armando Fortes , Yongwei Chen , Xingang Pan

While 3D generation is progressing rapidly, recent work has often focused on obtaining high-resolution assets, leaving user experience and deployability as afterthoughts. We present AssetGen, a 3D generator that focuses instead on these two…

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

Previous efforts have managed to generate production-ready 3D assets from text or images. However, these methods primarily employ NeRF or 3D Gaussian representations, which are not adept at producing smooth, high-quality geometries required…

Graphics · Computer Science 2024-10-15 Rengan Xie , Wenting Zheng , Kai Huang , Yizheng Chen , Qi Wang , Qi Ye , Wei Chen , Yuchi Huo

While neural 3D reconstruction has advanced substantially, its performance significantly degrades with sparse-view data, which limits its broader applicability, since SfM is often unreliable in sparse-view scenarios where feature matches…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Zhiwen Fan , Wenyan Cong , Kairun Wen , Kevin Wang , Jian Zhang , Xinghao Ding , Danfei Xu , Boris Ivanovic , Marco Pavone , Georgios Pavlakos , Zhangyang Wang , Yue Wang

Despite the promising results of multi-view reconstruction, the recent neural rendering-based methods, such as implicit surface rendering (IDR) and volume rendering (NeuS), not only incur a heavy computational burden on training but also…

Computer Vision and Pattern Recognition · Computer Science 2023-05-30 Yisu Zhang , Jianke Zhu , Lixiang Lin

4D mesh generation has recently emerged as a powerful paradigm for recovering dynamic 3D structure from videos, but existing methods remain slow, computationally expensive, and difficult to scale to longer sequences. We introduce a…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Dvir Samuel , Yuval Atzmon , Gal Chechik , Yoni Kasten

3D content generation has wide applications in various fields. One of its dominant paradigms is by sparse-view reconstruction using multi-view images generated by diffusion models. However, since directly reconstructing triangle meshes from…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Ruowen Zhao , Zhengyi Wang , Yikai Wang , Zihan Zhou , Jun Zhu

We propose a generative technique to edit 3D shapes, represented as meshes, NeRFs, or Gaussian Splats, in approximately 3 seconds, without the need for running an SDS type of optimization. Our key insight is to cast 3D editing as a…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Amir Barda , Matheus Gadelha , Vladimir G. Kim , Noam Aigerman , Amit H. Bermano , Thibault Groueix

3D content creation has achieved significant progress in terms of both quality and speed. Although current feed-forward models can produce 3D objects in seconds, their resolution is constrained by the intensive computation required during…

Computer Vision and Pattern Recognition · Computer Science 2024-02-08 Jiaxiang Tang , Zhaoxi Chen , Xiaokang Chen , Tengfei Wang , Gang Zeng , Ziwei Liu

3D assets are essential in the digital age. While automatic 3D generation, such as image-to-3d, has made significant strides in recent years, it often struggles to achieve fast, detailed, and high-fidelity generation simultaneously. In this…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Huanning Dong , Yinuo Huang , Fan Li , Ping Kuang

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

In the field of architecture, the conversion of single images into 2 and 1/2D and 3D meshes is a promising technology that enhances design visualization and efficiency. This paper evaluates four innovative methods: "One-2-3-45," "CRM:…

Graphics · Computer Science 2024-07-30 Jacob Sam , Karan Patel , Mike Saad

3D content generation has recently attracted significant research interest, driven by its critical applications in VR/AR and embodied AI. In this work, we tackle the challenging task of synthesizing multiple 3D assets within a single scene…

Computer Vision and Pattern Recognition · Computer Science 2025-12-10 Yanxu Meng , Haoning Wu , Ya Zhang , Weidi Xie

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
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