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The manipulation of latent space has recently become an interesting topic in the field of generative models. Recent research shows that latent directions can be used to manipulate images towards certain attributes. However, controlling the…

Computer Vision and Pattern Recognition · Computer Science 2022-02-15 Zehranaz Canfes , M. Furkan Atasoy , Alara Dirik , Pinar Yanardag

Recent advancements in text-to-3D generation have significantly contributed to the automation and democratization of 3D content creation. Building upon these developments, we aim to address the limitations of current methods in blending…

Computer Vision and Pattern Recognition · Computer Science 2024-08-26 Yeongtak Oh , Jooyoung Choi , Yongsung Kim , Minjun Park , Chaehun Shin , Sungroh Yoon

We present ShapeCrafter, a neural network for recursive text-conditioned 3D shape generation. Existing methods to generate text-conditioned 3D shapes consume an entire text prompt to generate a 3D shape in a single step. However, humans…

Computer Vision and Pattern Recognition · Computer Science 2023-04-11 Rao Fu , Xiao Zhan , Yiwen Chen , Daniel Ritchie , Srinath Sridhar

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

High-fidelity reconstruction of head avatars from monocular videos is highly desirable for virtual human applications, but it remains a challenge in the fields of computer graphics and computer vision. In this paper, we propose a two-phase…

Graphics · Computer Science 2025-03-31 Pilseo Park , Ze Zhang , Michel Sarkis , Ning Bi , Xiaoming Liu , Yiying Tong

We present a novel framework for enhancing the visual fidelity and consistency of text-guided 3D Gaussian Splatting (3DGS) editing. Existing editing approaches face two critical challenges: inconsistent geometric reconstructions across…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Xuanqi Zhang , Jieun Lee , Chris Joslin , Wonsook Lee

Text-to-image generative models, specifically those based on diffusion models like Imagen and Stable Diffusion, have made substantial advancements. Recently, there has been a surge of interest in the delicate refinement of text prompts.…

Computer Vision and Pattern Recognition · Computer Science 2024-04-08 Wenyi Mo , Tianyu Zhang , Yalong Bai , Bing Su , Ji-Rong Wen , Qing Yang

Mesh models have become increasingly accessible for numerous cities; however, the lack of realistic textures restricts their application in virtual urban navigation and autonomous driving. To address this, this paper proposes MeSS…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Xuyang Chen , Zhijun Zhai , Kaixuan Zhou , Zengmao Wang , Jianan He , Dong Wang , Yanfeng Zhang , mingwei Sun , Rüdiger Westermann , Konrad Schindler , Liqiu Meng

Reconstructing the 3D mesh of a general object from a single image is now possible thanks to the latest advances of deep learning technologies. However, due to the nontrivial difficulty of generating a feasible mesh structure, the…

Computer Vision and Pattern Recognition · Computer Science 2019-09-04 Junyi Pan , Xiaoguang Han , Weikai Chen , Jiapeng Tang , Kui Jia

We present a suite of techniques for jointly optimizing triangle meshes and shading models to match the appearance of reference scenes. This capability has a number of uses, including appearance-preserving simplification of extremely…

Graphics · Computer Science 2021-04-12 Jon Hasselgren , Jacob Munkberg , Jaakko Lehtinen , Miika Aittala , Samuli Laine

Local geometry-controllable computer-aided design (CAD) generation aims to modify local parts of CAD models automatically, enhancing design efficiency. It also ensures that the shapes of newly generated local parts follow user-specific…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Zhanwei Zhang , Kaiyuan Liu , Junjie Liu , Wenxiao Wang , Binbin Lin , Liang Xie , Chen Shen , Deng Cai

This paper aims to generate materials for 3D meshes from text descriptions. Unlike existing methods that synthesize texture maps, we propose to generate segment-wise procedural material graphs as the appearance representation, which…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Shangzan Zhang , Sida Peng , Tao Xu , Yuanbo Yang , Tianrun Chen , Nan Xue , Yujun Shen , Hujun Bao , Ruizhen Hu , Xiaowei Zhou

Well-designed prompts have demonstrated the potential to guide text-to-image models in generating amazing images. Although existing prompt engineering methods can provide high-level guidance, it is challenging for novice users to achieve…

Multimedia · Computer Science 2026-03-27 Nailei Hei , Qianyu Guo , Zihao Wang , Yan Wang , Haofen Wang , Wenqiang Zhang

Generating coherent and useful image/video scenes from a free-form textual description is technically a very difficult problem to handle. Textual description of the same scene can vary greatly from person to person, or sometimes even for…

Computer Vision and Pattern Recognition · Computer Science 2020-12-01 Faria Huq , Nafees Ahmed , Anindya Iqbal

We propose an approach to 3D reconstruction via inverse procedural modeling and investigate two variants of this approach. The first option consists in the fitting set of input parameters using a genetic algorithm. We demonstrate the…

Graphics · Computer Science 2023-10-23 Albert Garifullin , Nikolay Maiorov , Vladimir Frolov

Text-based 3D motion generation aims to automatically synthesize diverse motions from natural-language descriptions to extend user creativity, whereas motion editing modifies an existing motion sequence in response to text while preserving…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Sukhyun Jeong , Yong-Hoon Choi

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

Recent text-to-3D generation methods achieve impressive 3D content creation capacity thanks to the advances in image diffusion models and optimizing strategies. However, current methods struggle to generate correct 3D content for a complex…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Xinhua Cheng , Tianyu Yang , Jianan Wang , Yu Li , Lei Zhang , Jian Zhang , Li Yuan

This paper presents a methodology aiming at easing considerably the generation of high-quality meshes for complex 3D domains. We show that the whole mesh generation process can be controlled with only five parameters to generate in one…

Numerical Analysis · Mathematics 2020-09-10 Arthur Bawin , François Henrotte , Jean-François Remacle

Text-to-3D generation has shown great promise in generating novel 3D content based on given text prompts. However, existing generative methods mostly focus on geometric or visual plausibility while ignoring precise physics perception for…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Qingshan Xu , Jiao Liu , Melvin Wong , Caishun Chen , Yew-Soon Ong