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Related papers: Make-A-Texture: Fast Shape-Aware Texture Generatio…

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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

Novel photo-realistic texture synthesis is an important task for generating novel scenes, including asset generation for 3D simulations. However, to date, these methods predominantly generate textured objects in 2D space. If we rely on 2D…

Computer Vision and Pattern Recognition · Computer Science 2023-02-09 Dharma KC , Clayton T. Morrison , Bradley Walls

We provide a new model for texture synthesis based on a multiscale, multilayer feature extractor. Within the model, textures are represented by a set of statistics computed from ReLU wavelet coefficients at different layers, scales and…

Computer Vision and Pattern Recognition · Computer Science 2021-05-25 Jieqian He , Matthew Hirn

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

Object manipulation in images aims to not only edit the object's presentation but also gift objects with motion. Previous methods encountered challenges in concurrently handling static editing and dynamic generation, while also struggling…

Computer Vision and Pattern Recognition · Computer Science 2025-01-23 Ruisi Zhao , Zechuan Zhang , Zongxin Yang , Yi Yang

Despite having tremendous progress in image-to-3D generation, existing methods still struggle to produce multi-view consistent images with high-resolution textures in detail, especially in the paradigm of 2D diffusion that lacks 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-09-12 Haibo Yang , Yang Chen , Yingwei Pan , Ting Yao , Zhineng Chen , Chong-Wah Ngo , Tao Mei

We introduce a recipe for generating immersive 3D worlds from a single image by framing the task as an in-context learning problem for 2D inpainting models. This approach requires minimal training and uses existing generative models. Our…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Katja Schwarz , Denys Rozumnyi , Samuel Rota Bulò , Lorenzo Porzi , Peter Kontschieder

In this work, we propose a system that covers the complete workflow for achieving controlled authoring and editing of textures that present distinctive local characteristics. These include various effects that change the surface appearance…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 Andrei-Timotei Ardelean , Tim Weyrich

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

Most 3D generation research focuses on up-projecting 2D foundation models into the 3D space, either by minimizing 2D Score Distillation Sampling (SDS) loss or fine-tuning on multi-view datasets. Without explicit 3D priors, these methods…

Computer Vision and Pattern Recognition · Computer Science 2023-12-11 Lihe Ding , Shaocong Dong , Zhanpeng Huang , Zibin Wang , Yiyuan Zhang , Kaixiong Gong , Dan Xu , Tianfan Xue

Recently, text-to-image generation has exhibited remarkable advancements, with the ability to produce visually impressive results. In contrast, text-to-3D generation has not yet reached a comparable level of quality. Existing methods…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Yukang Cao , Yan-Pei Cao , Kai Han , Ying Shan , Kwan-Yee K. Wong

Automatic 3D generation has recently attracted widespread attention. Recent methods have greatly accelerated the generation speed, but usually produce less-detailed objects due to limited model capacity or 3D data. Motivated by recent…

Computer Vision and Pattern Recognition · Computer Science 2024-03-12 Zilong Chen , Yikai Wang , Feng Wang , Zhengyi Wang , Huaping Liu

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

Many deep learning based 3D face reconstruction methods have been proposed recently, however, few of them have applications in games. Current game character customization systems either require players to manually adjust considerable face…

Computer Vision and Pattern Recognition · Computer Science 2021-02-09 Jiangke Lin , Yi Yuan , Zhengxia Zou

Generating high-quality, photorealistic textures for 3D human avatars remains a fundamental yet challenging task in computer vision and multimedia field. However, real paired front and back images of human subjects are rarely available with…

Graphics · Computer Science 2026-04-10 Mingxiao Tu , Shuchang Ye , Hoijoon Jung , Jinman Kim

Facial texture generation is crucial for high-fidelity 3D face reconstruction from a single image. However, existing methods struggle to generate UV albedo maps with high-frequency details. To address this challenge, we propose a novel…

Computer Vision and Pattern Recognition · Computer Science 2025-06-17 Jiashu Dai , Along Wang , Binfan Ni , Tao Cao

We propose Make-A-Video -- an approach for directly translating the tremendous recent progress in Text-to-Image (T2I) generation to Text-to-Video (T2V). Our intuition is simple: learn what the world looks like and how it is described from…

Computer Vision and Pattern Recognition · Computer Science 2022-09-30 Uriel Singer , Adam Polyak , Thomas Hayes , Xi Yin , Jie An , Songyang Zhang , Qiyuan Hu , Harry Yang , Oron Ashual , Oran Gafni , Devi Parikh , Sonal Gupta , Yaniv Taigman

Coarse architectural models are often generated at scales ranging from individual buildings to scenes for downstream applications such as Digital Twin City, Metaverse, LODs, etc. Such piece-wise planar models can be abstracted as twins from…

Graphics · Computer Science 2023-09-21 Weidan Xiong , Hongqian Zhang , Botao Peng , Ziyu Hu , Yongli Wu , Jianwei Guo , Hui Huang

Recent works on text-to-3d generation show that using only 2D diffusion supervision for 3D generation tends to produce results with inconsistent appearances (e.g., faces on the back view) and inaccurate shapes (e.g., animals with extra…

Computer Vision and Pattern Recognition · Computer Science 2024-03-15 Cheng Chen , Xiaofeng Yang , Fan Yang , Chengzeng Feng , Zhoujie Fu , Chuan-Sheng Foo , Guosheng Lin , Fayao Liu

Video try-on replaces clothing in videos with target garments. Existing methods struggle to generate high-quality and temporally consistent results when handling complex clothing patterns and diverse body poses. We present 3DV-TON, a novel…

Computer Vision and Pattern Recognition · Computer Science 2025-04-25 Min Wei , Chaohui Yu , Jingkai Zhou , Fan Wang