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One of the major challenges in training text-to-image generation models is the need of a large number of high-quality image-text pairs. While image samples are often easily accessible, the associated text descriptions typically require…

Computer Vision and Pattern Recognition · Computer Science 2022-03-25 Yufan Zhou , Ruiyi Zhang , Changyou Chen , Chunyuan Li , Chris Tensmeyer , Tong Yu , Jiuxiang Gu , Jinhui Xu , Tong Sun

Large-scale pre-trained vision-language models allow for the zero-shot text-based generation of 3D avatars. The previous state-of-the-art method utilized CLIP to supervise neural implicit models that reconstructed a human body mesh.…

Computer Vision and Pattern Recognition · Computer Science 2023-09-15 Shuo Huang , Zongxin Yang , Liangting Li , Yi Yang , Jia Jia

We introduce SimAvatar, a framework designed to generate simulation-ready clothed 3D human avatars from a text prompt. Current text-driven human avatar generation methods either model hair, clothing, and the human body using a unified…

Computer Vision and Pattern Recognition · Computer Science 2024-12-20 Xueting Li , Ye Yuan , Shalini De Mello , Gilles Daviet , Jonathan Leaf , Miles Macklin , Jan Kautz , Umar Iqbal

In recent years, Generative Adversarial Networks (GANs) have improved steadily towards generating increasingly impressive real-world images. It is useful to steer the image generation process for purposes such as content creation. This can…

Computer Vision and Pattern Recognition · Computer Science 2020-05-12 David Stap , Maurits Bleeker , Sarah Ibrahimi , Maartje ter Hoeve

We present AvatarPopUp, a method for fast, high quality 3D human avatar generation from different input modalities, such as images and text prompts and with control over the generated pose and shape. The common theme is the use of…

Computer Vision and Pattern Recognition · Computer Science 2024-07-15 Nikos Kolotouros , Thiemo Alldieck , Enric Corona , Eduard Gabriel Bazavan , Cristian Sminchisescu

Model customization introduces new concepts to existing text-to-image models, enabling the generation of these new concepts/objects in novel contexts. However, such methods lack accurate camera view control with respect to the new object,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-04 Nupur Kumari , Grace Su , Richard Zhang , Taesung Park , Eli Shechtman , Jun-Yan Zhu

Text to Image Synthesis refers to the process of automatic generation of a photo-realistic image starting from a given text and is revolutionizing many real-world applications. In order to perform such process it is necessary to exploit…

Machine Learning · Computer Science 2019-10-10 Marco Menardi , Alex Falcon , Saida S. Mohamed , Lorenzo Seidenari , Giuseppe Serra , Alberto Del Bimbo , Carlo Tasso

Transferring the pose of a reference avatar to stylized 3D characters of various shapes is a fundamental task in computer graphics. Existing methods either require the stylized characters to be rigged, or they use the stylized character in…

Computer Vision and Pattern Recognition · Computer Science 2023-06-02 Jiashun Wang , Xueting Li , Sifei Liu , Shalini De Mello , Orazio Gallo , Xiaolong Wang , Jan Kautz

The generation of high-quality, animatable 3D head avatars from text has enormous potential in content creation applications such as games, movies, and embodied virtual assistants. Current text-to-3D generation methods typically combine…

Computer Vision and Pattern Recognition · Computer Science 2025-04-23 Yiqian Wu , Malte Prinzler , Xiaogang Jin , Siyu Tang

In this paper, we introduce GaussianMotion, a novel human rendering model that generates fully animatable scenes aligned with textual descriptions using Gaussian Splatting. Although existing methods achieve reasonable text-to-3D generation…

Computer Vision and Pattern Recognition · Computer Science 2025-02-18 Gyumin Shim , Sangmin Lee , Jaegul Choo

Leveraging Stable Diffusion for the generation of personalized portraits has emerged as a powerful and noteworthy tool, enabling users to create high-fidelity, custom character avatars based on their specific prompts. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2024-03-22 Siying Cui , Jia Guo , Xiang An , Jiankang Deng , Yongle Zhao , Xinyu Wei , Ziyong Feng

Image captioning requires numerous annotated image-text pairs, resulting in substantial annotation costs. Recently, large models (e.g. diffusion models and large language models) have excelled in producing high-quality images and text. This…

Computer Vision and Pattern Recognition · Computer Science 2023-12-20 Feipeng Ma , Yizhou Zhou , Fengyun Rao , Yueyi Zhang , Xiaoyan Sun

We introduce TADA, a simple-yet-effective approach that takes textual descriptions and produces expressive 3D avatars with high-quality geometry and lifelike textures, that can be animated and rendered with traditional graphics pipelines.…

Artificial Intelligence · Computer Science 2023-08-22 Tingting Liao , Hongwei Yi , Yuliang Xiu , Jiaxaing Tang , Yangyi Huang , Justus Thies , Michael J. Black

We present Face0, a novel way to instantaneously condition a text-to-image generation model on a face, in sample time, without any optimization procedures such as fine-tuning or inversions. We augment a dataset of annotated images with…

Computer Vision and Pattern Recognition · Computer Science 2023-06-13 Dani Valevski , Danny Wasserman , Yossi Matias , Yaniv Leviathan

Diffusion models are generative models with impressive text-to-image synthesis capabilities and have spurred a new wave of creative methods for classical machine learning tasks. However, the best way to harness the perceptual knowledge of…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Neehar Kondapaneni , Markus Marks , Manuel Knott , Rogerio Guimaraes , Pietro Perona

Building realistic and animatable avatars still requires minutes of multi-view or monocular self-rotating videos, and most methods lack precise control over gestures and expressions. To push this boundary, we address the challenge of…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Jun Xiang , Yudong Guo , Leipeng Hu , Boyang Guo , Yancheng Yuan , Juyong Zhang

We present a system for learning full-body neural avatars, i.e. deep networks that produce full-body renderings of a person for varying body pose and camera position. Our system takes the middle path between the classical graphics pipeline…

The recent wave of large-scale text-to-image diffusion models has dramatically increased our text-based image generation abilities. These models can generate realistic images for a staggering variety of prompts and exhibit impressive…

Machine Learning · Computer Science 2023-09-14 Alexander C. Li , Mihir Prabhudesai , Shivam Duggal , Ellis Brown , Deepak Pathak

Text-to-image generative models have become a prominent and powerful tool that excels at generating high-resolution realistic images. However, guiding the generative process of these models to consider detailed forms of conditioning…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Nick Stracke , Stefan Andreas Baumann , Joshua M. Susskind , Miguel Angel Bautista , Björn Ommer

This paper studies the task of full generative modelling of realistic images of humans, guided only by coarse sketch of the pose, while providing control over the specific instance or type of outfit worn by the user. This is a difficult…

Computer Vision and Pattern Recognition · Computer Science 2019-06-06 Xu Chen , Jie Song , Otmar Hilliges