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Recently, multi-view diffusion-based 3D generation methods have gained significant attention. However, these methods often suffer from shape and texture misalignment across generated multi-view images, leading to low-quality 3D generation…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Zhuojiang Cai , Yiheng Zhang , Meitong Guo , Mingdao Wang , Yuwang Wang

This paper introduces a novel approach to synthesize texture to dress up a given 3D object, given a text prompt. Based on the pretrained text-to-image (T2I) diffusion model, existing methods usually employ a project-and-inpaint approach, in…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Yuxin Liu , Minshan Xie , Hanyuan Liu , Tien-Tsin Wong

Recent advances in latent diffusion models have enabled exciting progress in image style transfer. However, several key issues remain. For example, existing methods still struggle to accurately match styles. They are often limited in the…

Computer Vision and Pattern Recognition · Computer Science 2025-08-19 Dan Ruta , Abdelaziz Djelouah , Raphael Ortiz , Christopher Schroers

The creation of high-quality 3D assets is paramount for applications in digital heritage preservation, entertainment, and robotics. Traditionally, this process necessitates skilled professionals and specialized software for the modeling,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Shen Chen , Jiale Zhou , Zhongyu Jiang , Tianfang Zhang , Zongkai Wu , Jenq-Neng Hwang , Lei Li

Style transfer of 3D faces has gained more and more attention. However, previous methods mainly use images of artistic faces for style transfer while ignoring arbitrary style images such as abstract paintings. To solve this problem, we…

Computer Vision and Pattern Recognition · Computer Science 2023-03-15 Xiangwen Deng , Yingshuang Zou , Yuanhao Cai , Chendong Zhao , Yang Liu , Zhifang Liu , Yuxiao Liu , Jiawei Zhou , Haoqian Wang

Recent advancements in 3D Gaussian Splatting (3DGS) and Neural Radiance Fields (NeRF) have achieved impressive results in real-time 3D reconstruction and novel view synthesis. However, these methods struggle in large-scale, unconstrained…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Niluthpol Chowdhury Mithun , Tuan Pham , Qiao Wang , Ben Southall , Kshitij Minhas , Bogdan Matei , Stephan Mandt , Supun Samarasekera , Rakesh Kumar

Style-guided texture generation aims to generate a texture that is harmonious with both the style of the reference image and the geometry of the input mesh, given a reference style image and a 3D mesh with its text description. Although…

Computer Vision and Pattern Recognition · Computer Science 2024-11-04 Zhiyu Xie , Yuqing Zhang , Xiangjun Tang , Yiqian Wu , Dehan Chen , Gongsheng Li , Xaogang Jin

Text-to-3D, known for its efficient generation methods and expansive creative potential, has garnered significant attention in the AIGC domain. However, the pixel-wise rendering of NeRF and its ray marching light sampling constrain the…

Computer Vision and Pattern Recognition · Computer Science 2024-11-27 Xinhai Li , Huaibin Wang , Kuo-Kun Tseng

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

3D stylization is central to game development, virtual reality, and digital arts, where the demand for diverse assets calls for scalable methods that support fast, high-fidelity manipulation. Existing text-to-3D stylization methods…

Computer Vision and Pattern Recognition · Computer Science 2025-12-04 Melis Ocal , Xiaoyan Xing , Yue Li , Ngo Anh Vien , Sezer Karaoglu , Theo Gevers

Transferring 2D textures onto complex 3D scenes plays a vital role in enhancing the efficiency and controllability of 3D multimedia content creation. However, existing 3D style transfer methods primarily focus on transferring abstract…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Wenjie Liu , Zhongliang Liu , Junwei Shu , Changbo Wang , Yang Li

Neural style transfer has drawn considerable attention from both academic and industrial field. Although visual effect and efficiency have been significantly improved, existing methods are unable to coordinate spatial distribution of visual…

Computer Vision and Pattern Recognition · Computer Science 2019-01-17 Yuan Yao , Jianqiang Ren , Xuansong Xie , Weidong Liu , Yong-Jin Liu , Jun Wang

Reconstructing 3D objects from extremely sparse views is a long-standing and challenging problem. While recent techniques employ image diffusion models for generating plausible images at novel viewpoints or for distilling pre-trained…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Zi-Xin Zou , Weihao Cheng , Yan-Pei Cao , Shi-Sheng Huang , Ying Shan , Song-Hai Zhang

Recent advancements in 3D generation are predominantly propelled by improvements in 3D-aware image diffusion models. These models are pretrained on Internet-scale image data and fine-tuned on massive 3D data, offering the capability of…

Computer Vision and Pattern Recognition · Computer Science 2024-10-03 Zeyu Yang , Zijie Pan , Chun Gu , Li Zhang

Diffusion models have demonstrated remarkable performance in image generation, particularly within the domain of style transfer. Prevailing style transfer approaches typically leverage pre-trained diffusion models' robust feature extraction…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Yeqi He , Liang Li , Zhiwen Yang , Xichun Sheng , Zhidong Zhao , Chenggang Yan

Style transfer combines the content of one signal with the style of another. It supports applications such as data augmentation and scenario simulation, helping machine learning models generalize in data-scarce domains. While well developed…

We present Stylos, a single-forward 3D Gaussian framework for 3D style transfer that operates on unposed content, from a single image to a multi-view collection, conditioned on a separate reference style image. Stylos synthesizes a stylized…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Hanzhou Liu , Jia Huang , Mi Lu , Srikanth Saripalli , Peng Jiang

Despite advances in neural rendering, due to the scarcity of high-quality 3D datasets and the inherent limitations of multi-view diffusion models, view synthesis and 3D model generation are restricted to low resolutions with suboptimal…

Computer Vision and Pattern Recognition · Computer Science 2025-04-30 Yihang Luo , Shangchen Zhou , Yushi Lan , Xingang Pan , Chen Change Loy

Gaussian Splatting has become a popular technique for various 3D Computer Vision tasks, including novel view synthesis, scene reconstruction, and dynamic scene rendering. However, the challenge of natural-looking object insertion, where the…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Vsevolod Skorokhodov , Nikita Durasov , Pascal Fua

Hairstyle transfer is a challenging task in the image editing field that modifies the hairstyle of a given face image while preserving its other appearance and background features. The existing hairstyle transfer approaches heavily rely on…

Computer Vision and Pattern Recognition · Computer Science 2024-12-23 Chaeyeon Chung , Sunghyun Park , Jeongho Kim , Jaegul Choo