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

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Mesh generation is a crucial step in numerical simulations, significantly impacting simulation accuracy and efficiency. However, generating meshes remains time-consuming and requires expensive computational resources. In this paper, we…

Graphics · Computer Science 2024-07-03 Jiaming Peng , Xinhai Chen , Jie Liu

Generating synthetic multi-view images from a text prompt is an essential bridge to generating synthetic 3D assets. In this work, we introduce RapidMV, a novel text-to-multi-view generative model that can produce 32 multi-view synthetic…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Seungwook Kim , Yichun Shi , Kejie Li , Minsu Cho , Peng Wang

We present Make-A-Texture, a new framework that efficiently synthesizes high-resolution texture maps from textual prompts for given 3D geometries. Our approach progressively generates textures that are consistent across multiple viewpoints…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Xiaoyu Xiang , Liat Sless Gorelik , Yuchen Fan , Omri Armstrong , Forrest Iandola , Yilei Li , Ita Lifshitz , Rakesh Ranjan

Sketching is an important activity in any design process. Designers and stakeholders share their ideas through hand-drawn sketches. These sketches are further used to create 3D models. Current methods to generate 3D models from sketches are…

Computer Vision and Pattern Recognition · Computer Science 2022-04-12 Nitish Bhardwaj , Dhornala Bharadwaj , Alpana Dubey

This paper propose iFlame, a novel transformer-based network architecture for mesh generation. While attention-based models have demonstrated remarkable performance in mesh generation, their quadratic computational complexity limits…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Hanxiao Wang , Biao Zhang , Weize Quan , Dong-Ming Yan , Peter Wonka

High dynamic range (HDR) novel view synthesis (NVS) aims to reconstruct HDR scenes from multi-exposure low dynamic range (LDR) images. Existing HDR pipelines heavily rely on known camera poses, well-initialized dense point clouds, and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Dingqiang Ye , Jiacong Xu , Jianglu Ping , Yuxiang Guo , Chao Fan , Vishal M. Patel

We introduce PixARMesh, a method to autoregressively reconstruct complete 3D indoor scene meshes directly from a single RGB image. Unlike prior methods that rely on implicit signed distance fields and post-hoc layout optimization, PixARMesh…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Xiang Zhang , Sohyun Yoo , Hongrui Wu , Chuan Li , Jianwen Xie , Zhuowen Tu

This technical report introduces TripoSR, a 3D reconstruction model leveraging transformer architecture for fast feed-forward 3D generation, producing 3D mesh from a single image in under 0.5 seconds. Building upon the LRM network…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Dmitry Tochilkin , David Pankratz , Zexiang Liu , Zixuan Huang , Adam Letts , Yangguang Li , Ding Liang , Christian Laforte , Varun Jampani , Yan-Pei Cao

There has been significant progress in personalized image synthesis with methods such as Textual Inversion, DreamBooth, and LoRA. Yet, their real-world applicability is hindered by high storage demands, lengthy fine-tuning processes, and…

Computer Vision and Pattern Recognition · Computer Science 2024-02-05 Qixun Wang , Xu Bai , Haofan Wang , Zekui Qin , Anthony Chen , Huaxia Li , Xu Tang , Yao Hu

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

Generating multi-view images based on text or single-image prompts is a critical capability for the creation of 3D content. Two fundamental questions on this topic are what data we use for training and how to ensure multi-view consistency.…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Qi Zuo , Xiaodong Gu , Lingteng Qiu , Yuan Dong , Zhengyi Zhao , Weihao Yuan , Rui Peng , Siyu Zhu , Zilong Dong , Liefeng Bo , Qixing Huang

Autoregressive models can generate high-quality 3D meshes by sequentially producing vertices and faces, but their token-by-token decoding results in slow inference, limiting practical use in interactive and large-scale applications. We…

Computer Vision and Pattern Recognition · Computer Science 2025-11-20 Tingrui Shen , Yiheng Zhang , Chen Tang , Chuan Ping , Zixing Zhao , Le Wan , Yuwang Wang , Ronggang Wang , Shengfeng He

Triangle meshes play a crucial role in 3D applications for efficient manipulation and rendering. While auto-regressive methods generate structured meshes by predicting discrete vertex tokens, they are often constrained by limited face…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Ruowen Zhao , Junliang Ye , Zhengyi Wang , Guangce Liu , Yiwen Chen , Yikai Wang , Jun Zhu

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

Single image 3D reconstruction is an important but challenging task that requires extensive knowledge of our natural world. Many existing methods solve this problem by optimizing a neural radiance field under the guidance of 2D diffusion…

Computer Vision and Pattern Recognition · Computer Science 2023-06-30 Minghua Liu , Chao Xu , Haian Jin , Linghao Chen , Mukund Varma T , Zexiang Xu , Hao Su

Recent advancements in open-world 3D object generation have been remarkable, with image-to-3D methods offering superior fine-grained control over their text-to-3D counterparts. However, most existing models fall short in simultaneously…

Computer Vision and Pattern Recognition · Computer Science 2023-11-15 Minghua Liu , Ruoxi Shi , Linghao Chen , Zhuoyang Zhang , Chao Xu , Xinyue Wei , Hansheng Chen , Chong Zeng , Jiayuan Gu , Hao Su

Recent advances in 3D scene reconstruction enable real-time viewing in virtual and augmented reality. To support interactive operations for better immersiveness, such as moving or editing objects, 3D scene inpainting methods are proposed to…

Computer Vision and Pattern Recognition · Computer Science 2025-06-13 Junqi You , Chieh Hubert Lin , Weijie Lyu , Zhengbo Zhang , Ming-Hsuan Yang

3D meshes are a fundamental representation widely used in computer science and engineering. In robotics, they are particularly valuable because they capture objects in a form that aligns directly with how robots interact with the physical…

Robotics · Computer Science 2026-01-01 Qian Wang , Omar Abdellall , Tony Gao , Xiatao Sun , Daniel Rakita

Neural Radiance Field (NeRF) based 3D reconstruction is highly desirable for immersive Augmented and Virtual Reality (AR/VR) applications, but achieving instant (i.e., < 5 seconds) on-device NeRF training remains a challenge. In this work,…

Hardware Architecture · Computer Science 2025-03-31 Sixu Li , Chaojian Li , Wenbo Zhu , Boyang Yu , Yang Zhao , Cheng Wan , Haoran You , Huihong Shi , Yingyan Celine Lin

This work explores expanding the capabilities of large language models (LLMs) pretrained on text to generate 3D meshes within a unified model. This offers key advantages of (1) leveraging spatial knowledge already embedded in LLMs, derived…

Machine Learning · Computer Science 2024-11-15 Zhengyi Wang , Jonathan Lorraine , Yikai Wang , Hang Su , Jun Zhu , Sanja Fidler , Xiaohui Zeng