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Unsupervised generation of 3D-aware clothed humans with various appearances and controllable geometries is important for creating virtual human avatars and other AR/VR applications. Existing methods are either limited to rigid object…

Computer Vision and Pattern Recognition · Computer Science 2022-11-29 Jianfeng Zhang , Zihang Jiang , Dingdong Yang , Hongyi Xu , Yichun Shi , Guoxian Song , Zhongcong Xu , Xinchao Wang , Jiashi Feng

Photorealistic editing of portraits is a challenging task as humans are very sensitive to inconsistencies in faces. We present an approach for high-quality intuitive editing of the camera viewpoint and scene illumination in a portrait…

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

This report introduces Make-A-Character 2, an advanced system for generating high-quality 3D characters from single portrait photographs, ideal for game development and digital human applications. Make-A-Character 2 builds upon its…

Computer Vision and Pattern Recognition · Computer Science 2025-01-16 Lin Liu , Yutong Wang , Jiahao Chen , Jianfang Li , Tangli Xue , Longlong Li , Jianqiang Ren , Liefeng Bo

Existing online 3D shape repositories contain thousands of 3D models but lack photorealistic appearance. We present an approach to automatically assign high-quality, realistic appearance models to large scale 3D shape collections. The key…

Graphics · Computer Science 2018-09-27 Keunhong Park , Konstantinos Rematas , Ali Farhadi , Steven M. Seitz

Realistic image manipulation is challenging because it requires modifying the image appearance in a user-controlled way, while preserving the realism of the result. Unless the user has considerable artistic skill, it is easy to "fall off"…

Computer Vision and Pattern Recognition · Computer Science 2018-12-18 Jun-Yan Zhu , Philipp Krähenbühl , Eli Shechtman , Alexei A. Efros

We propose a trait-specific image generation method that models forehead creases geometrically using B-spline and B\'ezier curves. This approach ensures the realistic generation of both principal creases and non-prominent crease patterns,…

Computer Vision and Pattern Recognition · Computer Science 2025-01-24 Abhishek Tandon , Geetanjali Sharma , Gaurav Jaswal , Aditya Nigam , Raghavendra Ramachandra

With the powerfulness of convolution neural networks (CNN), CNN based face reconstruction has recently shown promising performance in reconstructing detailed face shape from 2D face images. The success of CNN-based methods relies on a large…

Computer Vision and Pattern Recognition · Computer Science 2018-05-16 Yudong Guo , Juyong Zhang , Jianfei Cai , Boyi Jiang , Jianmin Zheng

In recent years, the role of image generative models in facial reenactment has been steadily increasing. Such models are usually subject-agnostic and trained on domain-wide datasets. The appearance of the reenacted individual is learned…

Computer Vision and Pattern Recognition · Computer Science 2023-07-13 Ariel Elazary , Yotam Nitzan , Daniel Cohen-Or

We propose an approach to generate images of people given a desired appearance and pose. Disentangled representations of pose and appearance are necessary to handle the compound variability in the resulting generated images. Hence, we…

Computer Vision and Pattern Recognition · Computer Science 2021-04-27 Mengyao Zhai , Ruizhi Deng , Jiacheng Chen , Lei Chen , Zhiwei Deng , Greg Mori

Here we introduce a new model of natural textures based on the feature spaces of convolutional neural networks optimised for object recognition. Samples from the model are of high perceptual quality demonstrating the generative power of…

Computer Vision and Pattern Recognition · Computer Science 2015-11-09 Leon A. Gatys , Alexander S. Ecker , Matthias Bethge

Sketch portrait generation benefits a wide range of applications such as digital entertainment and law enforcement. Although plenty of efforts have been dedicated to this task, several issues still remain unsolved for generating vivid and…

Computer Vision and Pattern Recognition · Computer Science 2017-10-05 Dongyu Zhang , Liang Lin , Tianshui Chen , Xian Wu , Wenwei Tan , Ebroul Izquierdo

We present a fully automatic system that can produce high-fidelity, photo-realistic 3D digital human heads with a consumer RGB-D selfie camera. The system only needs the user to take a short selfie RGB-D video while rotating his/her head,…

Computer Vision and Pattern Recognition · Computer Science 2021-06-30 Linchao Bao , Xiangkai Lin , Yajing Chen , Haoxian Zhang , Sheng Wang , Xuefei Zhe , Di Kang , Haozhi Huang , Xinwei Jiang , Jue Wang , Dong Yu , Zhengyou Zhang

3D human segmentation has seen noticeable progress in re-cent years. It, however, still remains a challenge to date. In this paper, weintroduce a deep patch-based method for 3D human segmentation. Wefirst extract a local surface patch for…

Computer Vision and Pattern Recognition · Computer Science 2020-07-14 Dongbo Zhang , Zheng Fang , Xuequan Lu , Hong Qin , Antonio Robles-Kelly , Chao Zhang , Ying He

Hair is a rich medium of visual and cultural expression, yet its digital modeling remains challenging due to the duality of fluidity and structure. Many existing generative approaches rely primarily on continuous diffusion fields, which…

Graphics · Computer Science 2026-05-12 Haimin Luo , Min Ouyang , Lan Xu , Jingyi Yu

Creating human avatars is a highly desirable yet challenging task. Recent advancements in radiance field rendering have achieved unprecedented photorealism and real-time performance for personalized dynamic human avatars. However, these…

Graphics · Computer Science 2025-09-09 Dongliang Cao , Guoxing Sun , Marc Habermann , Florian Bernard

Realistic hair strand generation is crucial for applications like computer graphics and virtual reality. While diffusion models can generate hairstyles from text or images, these inputs lack precision and user-friendliness. Instead, we…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Na Zhang , Moran Li , Chengming Xu , Han Feng , Xiaobin Hu , Jiangning Zhang , Weijian Cao , Chengjie Wang , Yanwei Fu

Despite the recent success of face image generation with GANs, conditional hair editing remains challenging due to the under-explored complexity of its geometry and appearance. In this paper, we present MichiGAN (Multi-Input-Conditioned…

Computer Vision and Pattern Recognition · Computer Science 2020-11-02 Zhentao Tan , Menglei Chai , Dongdong Chen , Jing Liao , Qi Chu , Lu Yuan , Sergey Tulyakov , Nenghai Yu

Creating realistic 3D head assets for virtual characters that match a precise artistic vision remains labor-intensive. We present a novel framework that streamlines this process by providing artists with intuitive control over generated 3D…

We present 3DGH, an unconditional generative model for 3D human heads with composable hair and face components. Unlike previous work that entangles the modeling of hair and face, we propose to separate them using a novel data representation…