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Related papers: HeadSculpt: Crafting 3D Head Avatars with Text

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Diffusion models have emerged as a powerful generative method, capable of producing stunning photo-realistic images from natural language descriptions. However, these models lack explicit control over the 3D structure in the generated…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Wufei Ma , Qihao Liu , Jiahao Wang , Angtian Wang , Xiaoding Yuan , Yi Zhang , Zihao Xiao , Guofeng Zhang , Beijia Lu , Ruxiao Duan , Yongrui Qi , Adam Kortylewski , Yaoyao Liu , Alan Yuille

Powered by large-scale text-to-image generation models, text-to-3D avatar generation has made promising progress. However, most methods fail to produce photorealistic results, limited by imprecise geometry and low-quality appearance.…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Yuanyou Xu , Zongxin Yang , Yi Yang

Diffusion models have demonstrated exceptional capabilities in generating a broad spectrum of visual content, yet their proficiency in rendering text is still limited: they often generate inaccurate characters or words that fail to blend…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Jianyi Zhang , Yufan Zhou , Jiuxiang Gu , Curtis Wigington , Tong Yu , Yiran Chen , Tong Sun , Ruiyi Zhang

Text-to-image generative models can generate high-quality humans, but realism is lost when generating hands. Common artifacts include irregular hand poses, shapes, incorrect numbers of fingers, and physically implausible finger…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Supreeth Narasimhaswamy , Uttaran Bhattacharya , Xiang Chen , Ishita Dasgupta , Saayan Mitra , Minh Hoai

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

We present a novel framework for generating high-quality, animatable 4D avatar from a single image. While recent advances have shown promising results in 4D avatar creation, existing methods either require extensive multiview data or…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Fei Yin , Mallikarjun B R , Chun-Han Yao , Rafał Mantiuk , Varun Jampani

Recent years have seen an explosion of work and interest in text-to-3D shape generation. Much of the progress is driven by advances in 3D representations, large-scale pretraining and representation learning for text and image data enabling…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Han-Hung Lee , Manolis Savva , Angel X. Chang

Over the past years, significant progress has been made in creating photorealistic and drivable 3D avatars solely from videos of real humans. However, a core remaining challenge is the fine-grained and user-friendly editing of clothing…

Computer Vision and Pattern Recognition · Computer Science 2024-08-29 Basavaraj Sunagad , Heming Zhu , Mohit Mendiratta , Adam Kortylewski , Christian Theobalt , Marc Habermann

3D head avatars built with neural implicit volumetric representations have achieved unprecedented levels of photorealism. However, the computational cost of these methods remains a significant barrier to their widespread adoption,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Ziqian Bai , Feitong Tan , Sean Fanello , Rohit Pandey , Mingsong Dou , Shichen Liu , Ping Tan , Yinda Zhang

Synthesizing high-quality 3D face models from natural language descriptions is very valuable for many applications, including avatar creation, virtual reality, and telepresence. However, little research ever tapped into this task. We argue…

Computer Vision and Pattern Recognition · Computer Science 2023-05-08 Menghua Wu , Hao Zhu , Linjia Huang , Yiyu Zhuang , Yuanxun Lu , Xun Cao

Controllable generation of 3D assets is important for many practical applications like content creation in movies, games and engineering, as well as in AR/VR. Recently, diffusion models have shown remarkable results in generation quality of…

Computer Vision and Pattern Recognition · Computer Science 2024-08-01 Philipp Schröppel , Christopher Wewer , Jan Eric Lenssen , Eddy Ilg , Thomas Brox

The ability to create realistic, animatable and relightable head avatars from casual video sequences would open up wide ranging applications in communication and entertainment. Current methods either build on explicit 3D morphable meshes…

Computer Vision and Pattern Recognition · Computer Science 2023-03-01 Yufeng Zheng , Wang Yifan , Gordon Wetzstein , Michael J. Black , Otmar Hilliges

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

Building 3D animatable head avatars from a single image is an important yet challenging problem. Existing methods generally collapse under large camera pose variations, compromising the realism of 3D avatars. In this work, we propose a new…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Shuling Zhao , Dan Xu

The remarkable progress in 3D face reconstruction has resulted in high-detail and photorealistic facial representations. Recently, Diffusion Models have revolutionized the capabilities of generative methods by surpassing the performance of…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Stathis Galanakis , Alexandros Lattas , Stylianos Moschoglou , Stefanos Zafeiriou

Creating high-quality animatable 3D human avatars from a single image remains a significant challenge in computer vision due to the inherent difficulty of reconstructing complete 3D information from a single viewpoint. Current approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-05-09 Yonwoo Choi

Traditionally, creating photo-realistic 3D head avatars requires a studio-level multi-view capture setup and expensive optimization during test-time, limiting the use of digital human doubles to the VFX industry or offline renderings. To…

Computer Vision and Pattern Recognition · Computer Science 2025-09-16 Tobias Kirschstein , Javier Romero , Artem Sevastopolsky , Matthias Nießner , Shunsuke Saito

Creating expressive, diverse and high-quality 3D avatars from highly customized text descriptions and pose guidance is a challenging task, due to the intricacy of modeling and texturing in 3D that ensure details and various styles…

Computer Vision and Pattern Recognition · Computer Science 2023-08-08 Huichao Zhang , Bowen Chen , Hao Yang , Liao Qu , Xu Wang , Li Chen , Chao Long , Feida Zhu , Kang Du , Min Zheng

We propose a 3D generation pipeline that uses diffusion models to generate realistic human digital avatars. Due to the wide variety of human identities, poses, and stochastic details, the generation of 3D human meshes has been a challenging…

Computer Vision and Pattern Recognition · Computer Science 2023-09-18 Byungjun Kim , Patrick Kwon , Kwangho Lee , Myunggi Lee , Sookwan Han , Daesik Kim , Hanbyul Joo

Reconstructing high-fidelity 3D head avatars is crucial in various applications such as virtual reality. The pioneering methods reconstruct realistic head avatars with Neural Radiance Fields (NeRF), which have been limited by training and…

Computer Vision and Pattern Recognition · Computer Science 2025-11-03 Peng Chen , Xiaobao Wei , Qingpo Wuwu , Xinyi Wang , Xingyu Xiao , Ming Lu
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