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The recent success of pre-trained diffusion models unlocks the possibility of the automatic generation of textures for arbitrary 3D meshes in the wild. However, these models are trained in the screen space, while converting them to a…

Computer Vision and Pattern Recognition · Computer Science 2024-06-28 Hongkun Zhang , Zherong Pan , Congyi Zhang , Lifeng Zhu , Xifeng Gao

We present a novel approach for single-image mesh texturing, which employs a diffusion model with judicious conditioning to seamlessly transfer an object's texture from a single RGB image to a given 3D mesh object. We do not assume that the…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Sai Raj Kishore Perla , Yizhi Wang , Ali Mahdavi-Amiri , Hao Zhang

Recently, text-guided 3D generative methods have made remarkable advancements in producing high-quality textures and geometry, capitalizing on the proliferation of large vision-language and image diffusion models. However, existing methods…

Computer Vision and Pattern Recognition · Computer Science 2023-08-30 Xiao Han , Yukang Cao , Kai Han , Xiatian Zhu , Jiankang Deng , Yi-Zhe Song , Tao Xiang , Kwan-Yee K. Wong

Text-to-image diffusion models pre-trained on billions of image-text pairs have recently enabled 3D content creation by optimizing a randomly initialized differentiable 3D representation with score distillation. However, the optimization…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Yukun Huang , Jianan Wang , Yukai Shi , Boshi Tang , Xianbiao Qi , Lei Zhang

We present Text2Room, a method for generating room-scale textured 3D meshes from a given text prompt as input. To this end, we leverage pre-trained 2D text-to-image models to synthesize a sequence of images from different poses. In order to…

Computer Vision and Pattern Recognition · Computer Science 2023-09-12 Lukas Höllein , Ang Cao , Andrew Owens , Justin Johnson , Matthias Nießner

Learning to generate textures for a novel 3D mesh given a collection of 3D meshes and real-world 2D images is an important problem with applications in various domains such as 3D simulation, augmented and virtual reality, gaming,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-08 Dharma KC , Clayton T. Morrison

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

Generating high-quality textures for 3D assets is a challenging task. Existing multiview texture generation methods suffer from the multiview inconsistency and missing textures on unseen parts, while UV inpainting texture methods do not…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Zheng Zhang , Qinchuan Zhang , Yuteng Ye , Zhi Chen , Penglei Ji , Mengfei Li , Wenxiao Zhang , Yuan Liu

With the widespread usage of VR devices and contents, demands for 3D scene generation techniques become more popular. Existing 3D scene generation models, however, limit the target scene to specific domain, primarily due to their training…

Computer Vision and Pattern Recognition · Computer Science 2023-11-27 Jaeyoung Chung , Suyoung Lee , Hyeongjin Nam , Jaerin Lee , Kyoung Mu Lee

We introduce DreamPolish, a text-to-3D generation model that excels in producing refined geometry and high-quality textures. In the geometry construction phase, our approach leverages multiple neural representations to enhance the stability…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Yean Cheng , Ziqi Cai , Ming Ding , Wendi Zheng , Shiyu Huang , Yuxiao Dong , Jie Tang , Boxin Shi

Recent advances in 3D content creation mostly leverage optimization-based 3D generation via score distillation sampling (SDS). Though promising results have been exhibited, these methods often suffer from slow per-sample optimization,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-01 Jiaxiang Tang , Jiawei Ren , Hang Zhou , Ziwei Liu , Gang Zeng

Current texture synthesis methods, which generate textures from fixed viewpoints, suffer from inconsistencies due to the lack of global context and geometric understanding. Meanwhile, recent advancements in video generation models have…

Graphics · Computer Science 2025-06-27 Donggoo Kang , Jangyeong Kim , Dasol Jeong , Junyoung Choi , Jeonga Wi , Hyunmin Lee , Joonho Gwon , Joonki Paik

Reconstructing real-world 3D objects has numerous applications in computer vision, such as virtual reality, video games, and animations. Ideally, 3D reconstruction methods should generate high-fidelity results with 3D consistency in…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Jingnan Gao , Zhuo Chen , Yichao Yan , Bowen Pan , Zhe Wang , Jiangjing Lyu , Xiaokang Yang

Textured 3D morphing creates smooth and plausible interpolation sequences between two 3D objects, focusing on transitions in both shape and texture. This is important for creative applications like visual effects in filmmaking. Previous…

Computer Vision and Pattern Recognition · Computer Science 2025-02-21 Songlin Yang , Yushi Lan , Honghua Chen , Xingang Pan

We present ShaDDR, an example-based deep generative neural network which produces a high-resolution textured 3D shape through geometry detailization and conditional texture generation applied to an input coarse voxel shape. Trained on a…

Computer Vision and Pattern Recognition · Computer Science 2023-11-23 Qimin Chen , Zhiqin Chen , Hang Zhou , Hao Zhang

Recent video inpainting algorithms integrate flow-based pixel propagation with transformer-based generation to leverage optical flow for restoring textures and objects using information from neighboring frames, while completing masked…

Computer Vision and Pattern Recognition · Computer Science 2025-01-20 Xiaowen Li , Haolan Xue , Peiran Ren , Liefeng Bo

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

Neural fields have achieved impressive advancements in view synthesis and scene reconstruction. However, editing these neural fields remains challenging due to the implicit encoding of geometry and texture information. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2023-09-08 Jingyu Zhuang , Chen Wang , Lingjie Liu , Liang Lin , Guanbin Li

We present Surf-D, a novel method for generating high-quality 3D shapes as Surfaces with arbitrary topologies using Diffusion models. Previous methods explored shape generation with different representations and they suffer from limited…

Computer Vision and Pattern Recognition · Computer Science 2024-07-25 Zhengming Yu , Zhiyang Dou , Xiaoxiao Long , Cheng Lin , Zekun Li , Yuan Liu , Norman Müller , Taku Komura , Marc Habermann , Christian Theobalt , Xin Li , Wenping Wang

This paper presents an extension to the KinectFusion algorithm which allows creating simplified 3D models with high quality RGB textures. This is achieved through (i) creating model textures using images from an HD RGB camera that is…

Graphics · Computer Science 2016-02-23 Song Liu , Wanqing Li , Philip Ogunbona , Yang-Wai Chow
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