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Text-guided human motion generation has drawn significant interest because of its impactful applications spanning animation and robotics. Recently, application of diffusion models for motion generation has enabled improvements in the…

Computer Vision and Pattern Recognition · Computer Science 2023-05-17 Samaneh Azadi , Akbar Shah , Thomas Hayes , Devi Parikh , Sonal Gupta

As the digital and physical worlds become more intertwined, there has been a lot of interest in digital avatars that closely resemble their real-world counterparts. Current digitization methods used in 3D production pipelines require costly…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Yifan Wang , Ivan Molodetskikh , Ondrej Texler , Dimitar Dinev

Generating 3D human models directly from text helps reduce the cost and time of character modeling. However, achieving multi-attribute controllable and realistic 3D human avatar generation is still challenging due to feature coupling and…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Chaoqun Gong , Yuqin Dai , Ronghui Li , Achun Bao , Jun Li , Jian Yang , Yachao Zhang , Xiu Li

Two major approaches exist for creating animatable human avatars. The first, a 3D-based approach, optimizes a NeRF- or 3DGS-based avatar from videos of a single person, achieving personalization through a disentangled identity…

Computer Vision and Pattern Recognition · Computer Science 2025-08-14 Geonhee Sim , Gyeongsik Moon

Recent text-to-video generation approaches rely on computationally heavy training and require large-scale video datasets. In this paper, we introduce a new task of zero-shot text-to-video generation and propose a low-cost approach (without…

Computer Vision and Pattern Recognition · Computer Science 2023-03-24 Levon Khachatryan , Andranik Movsisyan , Vahram Tadevosyan , Roberto Henschel , Zhangyang Wang , Shant Navasardyan , Humphrey Shi

In a surge of text-to-image (T2I) models and their customization methods that generate new images of a user-provided subject, current works focus on alleviating the costs incurred by a lengthy per-subject optimization. These zero-shot…

Computer Vision and Pattern Recognition · Computer Science 2024-03-22 Yeji Song , Jimyeong Kim , Wonhark Park , Wonsik Shin , Wonjong Rhee , Nojun Kwak

We present DreamAvatar, a text-and-shape guided framework for generating high-quality 3D human avatars with controllable poses. While encouraging results have been reported by recent methods on text-guided 3D common object generation,…

Computer Vision and Pattern Recognition · Computer Science 2023-12-01 Yukang Cao , Yan-Pei Cao , Kai Han , Ying Shan , Kwan-Yee K. Wong

We propose TextToon, a method to generate a drivable toonified avatar. Given a short monocular video sequence and a written instruction about the avatar style, our model can generate a high-fidelity toonified avatar that can be driven in…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Luchuan Song , Lele Chen , Celong Liu , Pinxin Liu , Chenliang Xu

Recent advances in personalized image generation allow a pre-trained text-to-image model to learn a new concept from a set of images. However, existing personalization approaches usually require heavy test-time finetuning for each concept,…

Computer Vision and Pattern Recognition · Computer Science 2023-04-10 Jing Shi , Wei Xiong , Zhe Lin , Hyun Joon Jung

We introduce Visual Persona, a foundation model for text-to-image full-body human customization that, given a single in-the-wild human image, generates diverse images of the individual guided by text descriptions. Unlike prior methods that…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Jisu Nam , Soowon Son , Zhan Xu , Jing Shi , Difan Liu , Feng Liu , Aashish Misraa , Seungryong Kim , Yang Zhou

3D avatar creation plays a crucial role in the digital age. However, the whole production process is prohibitively time-consuming and labor-intensive. To democratize this technology to a larger audience, we propose AvatarCLIP, a zero-shot…

Computer Vision and Pattern Recognition · Computer Science 2022-05-18 Fangzhou Hong , Mingyuan Zhang , Liang Pan , Zhongang Cai , Lei Yang , Ziwei Liu

Recent progress in personalized image generation using diffusion models has been significant. However, development in the area of open-domain and non-fine-tuning personalized image generation is proceeding rather slowly. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2024-05-21 Jian Ma , Junhao Liang , Chen Chen , Haonan Lu

We present a novel, zero-shot pipeline for creating hyperrealistic, identity-preserving 3D avatars from a few unstructured phone images. Existing methods face several challenges: single-view approaches suffer from geometric inconsistencies…

We present DreamHuman, a method to generate realistic animatable 3D human avatar models solely from textual descriptions. Recent text-to-3D methods have made considerable strides in generation, but are still lacking in important aspects.…

Computer Vision and Pattern Recognition · Computer Science 2023-06-16 Nikos Kolotouros , Thiemo Alldieck , Andrei Zanfir , Eduard Gabriel Bazavan , Mihai Fieraru , Cristian Sminchisescu

Text-to-image models have made significant strides, producing impressive results in generating images from textual descriptions. However, creating a scalable pipeline for deploying these models in production remains a challenge. Achieving…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Parmida Atighehchian , Henry Wang , Andrei Kapustin , Boris Lerner , Tiancheng Jiang , Taylor Jensen , Negin Sokhandan

We present DreamBooth3D, an approach to personalize text-to-3D generative models from as few as 3-6 casually captured images of a subject. Our approach combines recent advances in personalizing text-to-image models (DreamBooth) with…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Amit Raj , Srinivas Kaza , Ben Poole , Michael Niemeyer , Nataniel Ruiz , Ben Mildenhall , Shiran Zada , Kfir Aberman , Michael Rubinstein , Jonathan Barron , Yuanzhen Li , Varun Jampani

Traditional methods for constructing high-quality, personalized head avatars from monocular videos demand extensive face captures and training time, posing a significant challenge for scalability. This paper introduces a novel approach to…

Computer Vision and Pattern Recognition · Computer Science 2024-02-20 Zhixuan Yu , Ziqian Bai , Abhimitra Meka , Feitong Tan , Qiangeng Xu , Rohit Pandey , Sean Fanello , Hyun Soo Park , Yinda Zhang

Incorporating a customized object into image generation presents an attractive feature in text-to-image generation. However, existing optimization-based and encoder-based methods are hindered by drawbacks such as time-consuming…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Ziyang Yuan , Mingdeng Cao , Xintao Wang , Zhongang Qi , Chun Yuan , Ying Shan

Current talking face generation methods mainly focus on speech-lip synchronization. However, insufficient investigation on the facial talking style leads to a lifeless and monotonous avatar. Most previous works fail to imitate expressive…

Computer Vision and Pattern Recognition · Computer Science 2024-11-21 Liyang Chen , Zhiyong Wu , Runnan Li , Weihong Bao , Jun Ling , Xu Tan , Sheng Zhao

In high-end visual effects pipelines, a customized (and expensive) light stage system is (typically) used to scan an actor in order to acquire both geometry and texture for various expressions. Aiming towards democratization, we propose a…

Graphics · Computer Science 2024-01-31 Yilin Zhu , Dalton Omens , Haodi He , Ron Fedkiw