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Recent deep learning methods can generate diverse graphic design layouts efficiently. However, these methods often create layouts with flaws, such as misalignment, unwanted overlaps, and unsatisfied containment. To tackle this issue, we…

Graphics · Computer Science 2025-08-26 I-Chao Shen , Ariel Shamir , Takeo Igarashi

3D generation has witnessed significant advancements, yet efficiently producing high-quality 3D assets from a single image remains challenging. In this paper, we present a triplane autoencoder, which encodes 3D models into a compact…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Bowen Zhang , Tianyu Yang , Yu Li , Lei Zhang , Xi Zhao

This paper presents a novel method for building scalable 3D generative models utilizing pre-trained video diffusion models. The primary obstacle in developing foundation 3D generative models is the limited availability of 3D data. Unlike…

Computer Vision and Pattern Recognition · Computer Science 2024-07-22 Junlin Han , Filippos Kokkinos , Philip Torr

We present GALA3D, generative 3D GAussians with LAyout-guided control, for effective compositional text-to-3D generation. We first utilize large language models (LLMs) to generate the initial layout and introduce a layout-guided 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-06-12 Xiaoyu Zhou , Xingjian Ran , Yajiao Xiong , Jinlin He , Zhiwei Lin , Yongtao Wang , Deqing Sun , Ming-Hsuan Yang

Over the last years, 3D morphable models (3DMMs) have emerged as a state-of-the-art methodology for modeling and generating expressive 3D avatars. However, given their reliance on a strict topology, along with their linear nature, they…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Rolandos Alexandros Potamias , Stathis Galanakis , Jiankang Deng , Athanasios Papaioannou , Stefanos Zafeiriou

Generating artistic and coherent 3D scene layouts is crucial in digital content creation. Traditional optimization-based methods are often constrained by cumbersome manual rules, while deep generative models face challenges in producing…

Computer Vision and Pattern Recognition · Computer Science 2025-10-20 Xiaoming Zhu , Xu Huang , Qinghongbing Xie , Zhi Deng , Junsheng Yu , Yirui Guan , Zhongyuan Liu , Lin Zhu , Qijun Zhao , Ligang Liu , Long Zeng

Text-to-3D is an emerging task that allows users to create 3D content with infinite possibilities. Existing works tackle the problem by optimizing a 3D representation with guidance from pre-trained diffusion models. An apparent drawback is…

Computer Vision and Pattern Recognition · Computer Science 2023-06-06 Yiji Cheng , Fei Yin , Xiaoke Huang , Xintong Yu , Jiaxiang Liu , Shikun Feng , Yujiu Yang , Yansong Tang

Recent progress in 3D object generation has greatly improved both the quality and efficiency. However, most existing methods generate a single mesh with all parts fused together, which limits the ability to edit or manipulate individual…

Computer Vision and Pattern Recognition · Computer Science 2025-06-12 Jiaxiang Tang , Ruijie Lu , Zhaoshuo Li , Zekun Hao , Xuan Li , Fangyin Wei , Shuran Song , Gang Zeng , Ming-Yu Liu , Tsung-Yi Lin

Facial expression editing methods can be mainly categorized into two types based on their architectures: 2D-based and 3D-based methods. The former lacks 3D face modeling capabilities, making it difficult to edit 3D factors effectively. The…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Yikang He , Jichao Zhang , Wei Wang , Nicu Sebe , Yao Zhao

Although recent 3D-native generators have made great progress in synthesizing reliable geometry, they still fall short in achieving realistic appearances. A key obstacle lies in the lack of diverse and high-quality real-world 3D assets with…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Xinyue Liang , Zhinyuan Ma , Lingchen Sun , Yanjun Guo , Lei Zhang

Impressive progress in generative models and implicit representations gave rise to methods that can generate 3D shapes of high quality. However, being able to locally control and edit shapes is another essential property that can unlock…

Computer Vision and Pattern Recognition · Computer Science 2023-03-22 Konstantinos Tertikas , Despoina Paschalidou , Boxiao Pan , Jeong Joon Park , Mikaela Angelina Uy , Ioannis Emiris , Yannis Avrithis , Leonidas Guibas

We propose a novel framework for simultaneously generating and manipulating the face images with desired attributes. While the state-of-the-art attribute editing technique has achieved the impressive performance for creating realistic…

Computer Vision and Pattern Recognition · Computer Science 2018-10-01 Kyungjune Baek , Duhyeon Bang , Hyunjung Shim

Graphic design visually conveys information and data by creating and combining text, images and graphics. Two-stage methods that rely primarily on layout generation lack creativity and intelligence, making graphic design still…

Computer Vision and Pattern Recognition · Computer Science 2025-07-15 Yadong Qu , Shancheng Fang , Yuxin Wang , Xiaorui Wang , Zhineng Chen , Hongtao Xie , Yongdong Zhang

Recent breakthroughs in single-image 3D portrait reconstruction have enabled telepresence systems to stream 3D portrait videos from a single camera in real-time, potentially democratizing telepresence. However, per-frame 3D reconstruction…

Computer Vision and Pattern Recognition · Computer Science 2024-05-03 Shengze Wang , Xueting Li , Chao Liu , Matthew Chan , Michael Stengel , Josef Spjut , Henry Fuchs , Shalini De Mello , Koki Nagano

High-quality textures are critical for realistic 3D content creation, yet existing generative methods are slow, rely on UV maps, and often fail to remain faithful to a reference image. To address these challenges, we propose a…

Computer Vision and Pattern Recognition · Computer Science 2025-09-08 Arianna Rampini , Kanika Madan , Bruno Roy , AmirHossein Zamani , Derek Cheung

Although manipulating facial attributes by Generative Adversarial Networks (GANs) has been remarkably successful recently, there are still some challenges in explicit control of features such as pose, expression, lighting, etc. Recent…

Computer Vision and Pattern Recognition · Computer Science 2022-09-27 Yuanming Li , Jeong-gi Kwak , David Han , Hanseok Ko

Image synthesis via Generative Adversarial Networks (GANs) of three-dimensional (3D) medical images has great potential that can be extended to many medical applications, such as, image enhancement and disease progression modeling. However,…

Image and Video Processing · Electrical Eng. & Systems 2021-07-22 Sungmin Hong , Razvan Marinescu , Adrian V. Dalca , Anna K. Bonkhoff , Martin Bretzner , Natalia S. Rost , Polina Golland

Single-image 3D generation has emerged as a prominent research topic, playing a vital role in virtual reality, 3D modeling, and digital content creation. However, existing methods face challenges such as a lack of multi-view geometric…

Computer Vision and Pattern Recognition · Computer Science 2025-02-25 Jinbo Yan , Alan Zhao , Yixin Hu

In recent years, there has been significant progress in 2D generative face models fueled by applications such as animation, synthetic data generation, and digital avatars. However, due to the absence of 3D information, these 2D models often…

Computer Vision and Pattern Recognition · Computer Science 2023-10-30 Aashish Rai , Hiresh Gupta , Ayush Pandey , Francisco Vicente Carrasco , Shingo Jason Takagi , Amaury Aubel , Daeil Kim , Aayush Prakash , Fernando de la Torre

Auto-regressive models have achieved impressive results in 2D image generation by modeling joint distributions in grid space. In this paper, we extend auto-regressive models to 3D domains, and seek a stronger ability of 3D shape generation…

Computer Vision and Pattern Recognition · Computer Science 2024-03-27 Xuelin Qian , Yu Wang , Simian Luo , Yinda Zhang , Ying Tai , Zhenyu Zhang , Chengjie Wang , Xiangyang Xue , Bo Zhao , Tiejun Huang , Yunsheng Wu , Yanwei Fu
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