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Related papers: EASI-Tex: Edge-Aware Mesh Texturing from Single Im…

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Recent advancements in large-scale text-to-image diffusion models have enabled many applications in image editing. However, none of these methods have been able to edit the layout of single existing images. To address this gap, we propose…

Computer Vision and Pattern Recognition · Computer Science 2023-06-23 Zhiyuan Zhang , Zhitong Huang , Jing Liao

Given a 3D mesh with a UV parameterization, we introduce a novel approach to generating textures from text prompts. While prior work uses optimization from Text-to-Image Diffusion models to generate textures and geometry, this is slow and…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Julian Knodt , Xifeng Gao

We introduce a framework for intrinsic latent diffusion models operating directly on the surfaces of 3D shapes, with the goal of synthesizing high-quality textures. Our approach is underpinned by two contributions: field latents, a latent…

Computer Vision and Pattern Recognition · Computer Science 2024-05-30 Thomas W. Mitchel , Carlos Esteves , Ameesh Makadia

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

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

In this paper, we present TEXTure, a novel method for text-guided generation, editing, and transfer of textures for 3D shapes. Leveraging a pretrained depth-to-image diffusion model, TEXTure applies an iterative scheme that paints a 3D…

Computer Vision and Pattern Recognition · Computer Science 2023-02-06 Elad Richardson , Gal Metzer , Yuval Alaluf , Raja Giryes , Daniel Cohen-Or

We propose a diffusion-based approach for Text-to-Image (T2I) generation with consistent and interactive 3D layout control and editing. While prior methods improve spatial adherence using 2D cues or iterative copy-warp-paste strategies,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Andrea Rigo , Luca Stornaiuolo , Weijie Wang , Mauro Martino , Bruno Lepri , Nicu Sebe

We present TextureDreamer, a novel image-guided texture synthesis method to transfer relightable textures from a small number of input images (3 to 5) to target 3D shapes across arbitrary categories. Texture creation is a pivotal challenge…

Computer Vision and Pattern Recognition · Computer Science 2024-01-18 Yu-Ying Yeh , Jia-Bin Huang , Changil Kim , Lei Xiao , Thu Nguyen-Phuoc , Numair Khan , Cheng Zhang , Manmohan Chandraker , Carl S Marshall , Zhao Dong , Zhengqin Li

Recently, the impressive generative capabilities of diffusion models have been demonstrated, producing images with remarkable fidelity. Particularly, existing methods for the 3D object generation tasks, which is one of the fastest-growing…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Jaeseok Lee , Jaekoo Lee

We propose a novel image editing technique that enables 3D manipulations on single images, such as object rotation and translation. Existing 3D-aware image editing approaches typically rely on synthetic multi-view datasets for training…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Ruicheng Wang , Jianfeng Xiang , Jiaolong Yang , Xin Tong

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

In this work, we introduce Wonder3D, a novel method for efficiently generating high-fidelity textured meshes from single-view images.Recent methods based on Score Distillation Sampling (SDS) have shown the potential to recover 3D geometry…

Computer Vision and Pattern Recognition · Computer Science 2023-11-10 Xiaoxiao Long , Yuan-Chen Guo , Cheng Lin , Yuan Liu , Zhiyang Dou , Lingjie Liu , Yuexin Ma , Song-Hai Zhang , Marc Habermann , Christian Theobalt , Wenping Wang

Recent works on diffusion models have demonstrated a strong capability for conditioning image generation, e.g., text-guided image synthesis. Such success inspires many efforts trying to use large-scale pre-trained diffusion models for…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Zhixing Zhang , Ligong Han , Arnab Ghosh , Dimitris Metaxas , Jian Ren

Recent advances in text-to-image diffusion models have substantially improved the quality of image customization, enabling the synthesis of highly realistic images. Despite this progress, achieving fast and efficient personalization remains…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Aniket Roy , Maitreya Suin , Rama Chellappa

Recent advances in diffusion transformers have shown remarkable generalization in visual synthesis, yet most dense perception methods still rely on text-to-image (T2I) generators designed for stochastic generation. We revisit this paradigm…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Yiqing Shi , Yiren Song , Mike Zheng Shou

We present Text2Tex, a novel method for generating high-quality textures for 3D meshes from the given text prompts. Our method incorporates inpainting into a pre-trained depth-aware image diffusion model to progressively synthesize high…

Computer Vision and Pattern Recognition · Computer Science 2023-03-22 Dave Zhenyu Chen , Yawar Siddiqui , Hsin-Ying Lee , Sergey Tulyakov , Matthias Nießner

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

3D object generation from a single image involves estimating the full 3D geometry and texture of unseen views from an unposed RGB image captured in the wild. Accurately reconstructing an object's complete 3D structure and texture has…

Computer Vision and Pattern Recognition · Computer Science 2024-11-21 Hritam Basak , Hadi Tabatabaee , Shreekant Gayaka , Ming-Feng Li , Xin Yang , Cheng-Hao Kuo , Arnie Sen , Min Sun , Zhaozheng Yin

Text-guided image editing has recently experienced rapid development. However, simultaneously performing multiple editing actions on a single image, such as background replacement and specific subject attribute changes, while maintaining…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Pengzhi Li , QInxuan Huang , Yikang Ding , Zhiheng Li

Generating high-quality 3D objects from textual descriptions remains a challenging problem due to computational cost, the scarcity of 3D data, and complex 3D representations. We introduce Geometry Image Diffusion (GIMDiffusion), a novel…

Computer Vision and Pattern Recognition · Computer Science 2024-09-06 Slava Elizarov , Ciara Rowles , Simon Donné
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