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Texturing is a crucial step in the 3D asset production workflow, which enhances the visual appeal and diversity of 3D assets. Despite recent advancements in Text-to-Texture (T2T) generation, existing methods often yield subpar results,…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Wei Cheng , Juncheng Mu , Xianfang Zeng , Xin Chen , Anqi Pang , Chi Zhang , Zhibin Wang , Bin Fu , Gang Yu , Ziwei Liu , Liang Pan

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

Generating high-fidelity, 3D-consistent garment textures remains a challenging problem due to the inherent complexities of garment structures and the stringent requirement for detailed, globally consistent texture synthesis. Existing…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Jinbo Wu , Xiaobo Gao , Xing Liu , Chen Zhao , Jialun Liu

Diffusion-based methods have achieved prominent success in generating 2D media. However, accomplishing similar proficiencies for scene-level mesh texturing in 3D spatial applications, e.g., XR/VR, remains constrained, primarily due to the…

Computer Vision and Pattern Recognition · Computer Science 2023-10-23 Bangbang Yang , Wenqi Dong , Lin Ma , Wenbo Hu , Xiao Liu , Zhaopeng Cui , Yuewen Ma

We present a method for generating consistent novel views from a single source image. Our approach focuses on maximizing the reuse of visible pixels from the source image. To achieve this, we use a monocular depth estimator that transfers…

Computer Vision and Pattern Recognition · Computer Science 2023-10-26 Yash Kant , Aliaksandr Siarohin , Michael Vasilkovsky , Riza Alp Guler , Jian Ren , Sergey Tulyakov , Igor Gilitschenski

The advancement of diffusion models has pushed the boundary of text-to-3D object generation. While it is straightforward to composite objects into a scene with reasonable geometry, it is nontrivial to texture such a scene perfectly due to…

Computer Vision and Pattern Recognition · Computer Science 2024-06-05 Qi Wang , Ruijie Lu , Xudong Xu , Jingbo Wang , Michael Yu Wang , Bo Dai , Gang Zeng , Dan Xu

Texture map production is an important part of 3D modeling and determines the rendering quality. Recently, diffusion-based methods have opened a new way for texture generation. However, restricted control flexibility and limited prompt…

Graphics · Computer Science 2025-06-04 Dongyu Yan , Leyi Wu , Jiantao Lin , Luozhou Wang , Tianshuo Xu , Zhifei Chen , Zhen Yang , Lie Xu , Shunsi Zhang , Yingcong Chen

Recently, significant advances have been made in 3D object generation. Building upon the generated geometry, current pipelines typically employ image diffusion models to generate multi-view RGB images, followed by UV texture reconstruction…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Mingqi Shao , Feng Xiong , Zhaoxu Sun , Mu Xu

3D Gaussian inpainting, a critical technique for numerous applications in virtual reality and multimedia, has made significant progress with pretrained diffusion models. However, ensuring multi-view consistency, an essential requirement for…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Yuxin Cheng , Binxiao Huang , Taiqiang Wu , Wenyong Zhou , Chenchen Ding , Zhengwu Liu , Graziano Chesi , Ngai Wong

As online shopping is growing, the ability for buyers to virtually visualize products in their settings-a phenomenon we define as "Virtual Try-All"-has become crucial. Recent diffusion models inherently contain a world model, rendering them…

Computer Vision and Pattern Recognition · Computer Science 2024-01-26 Mehmet Saygin Seyfioglu , Karim Bouyarmane , Suren Kumar , Amir Tavanaei , Ismail B. Tutar

The techniques for 3D indoor scene capturing are widely used, but the meshes produced leave much to be desired. In this paper, we propose "RoomDreamer", which leverages powerful natural language to synthesize a new room with a different…

Computer Vision and Pattern Recognition · Computer Science 2023-05-22 Liangchen Song , Liangliang Cao , Hongyu Xu , Kai Kang , Feng Tang , Junsong Yuan , Yang Zhao

Image inpainting is the task of reconstructing missing or damaged parts of an image in a way that seamlessly blends with the surrounding content. With the advent of advanced generative models, especially diffusion models and generative…

Computer Vision and Pattern Recognition · Computer Science 2025-06-17 Xingzhong Hou , Jie Wu , Boxiao Liu , Yi Zhang , Guanglu Song , Yunpeng Liu , Yu Liu , Haihang You

Existing inpainting methods often require extensive retraining or fine-tuning to integrate new content seamlessly, yet they struggle to maintain coherence in both structure and style between inpainted regions and the surrounding background.…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Ying Li , Xinzhe Li , Yong Du , Yangyang Xu , Junyu Dong , Shengfeng He

We propose SceneTex, a novel method for effectively generating high-quality and style-consistent textures for indoor scenes using depth-to-image diffusion priors. Unlike previous methods that either iteratively warp 2D views onto a mesh…

Computer Vision and Pattern Recognition · Computer Science 2023-11-30 Dave Zhenyu Chen , Haoxuan Li , Hsin-Ying Lee , Sergey Tulyakov , Matthias Nießner

Image inpainting refers to the task of generating a complete, natural image based on a partially revealed reference image. Recently, many research interests have been focused on addressing this problem using fixed diffusion models. These…

Computer Vision and Pattern Recognition · Computer Science 2023-04-10 Guanhua Zhang , Jiabao Ji , Yang Zhang , Mo Yu , Tommi Jaakkola , Shiyu Chang

Generating high-quality textures for 3D scenes is crucial for applications in interior design, gaming, and augmented/virtual reality (AR/VR). Although recent advancements in 3D generative models have enhanced content creation, significant…

Computer Vision and Pattern Recognition · Computer Science 2025-01-27 Yunfan Zhang , Zhiwei Xiong , Zhiqi Shen , Guosheng Lin , Hao Wang , Nicolas Vun

3D meshes are widely used in computer vision and graphics for their efficiency in animation and minimal memory use, playing a crucial role in movies, games, AR, and VR. However, creating temporally consistent and realistic textures for mesh…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Jingzhi Bao , Xueting Li , Ming-Hsuan Yang

High-quality 3D streaming from multiple cameras is crucial for immersive experiences in many AR/VR applications. The limited number of views - often due to real-time constraints - leads to missing information and incomplete surfaces in the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-06 Leif Van Holland , Domenic Zingsheim , Mana Takhsha , Hannah Dröge , Patrick Stotko , Markus Plack , Reinhard Klein

Neural reconstruction approaches are rapidly emerging as the preferred representation for 3D scenes, but their limited editability is still posing a challenge. In this work, we propose an approach for 3D scene inpainting -- the task of…

Computer Vision and Pattern Recognition · Computer Science 2024-04-17 Ashkan Mirzaei , Riccardo De Lutio , Seung Wook Kim , David Acuna , Jonathan Kelly , Sanja Fidler , Igor Gilitschenski , Zan Gojcic

Although diffusion models exhibit impressive generative capabilities, existing methods for stylized image generation based on these models often require textual inversion or fine-tuning with style images, which is time-consuming and limits…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Xin Ma , Yaohui Wang , Xinyuan Chen , Tien-Tsin Wong , Cunjian Chen
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