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Most real-world image editing tasks require multiple sequential edits to achieve desired results. Current editing approaches, primarily designed for single-object modifications, struggle with sequential editing: especially with maintaining…

Computer Vision and Pattern Recognition · Computer Science 2025-05-05 Daneul Kim , Jaeah Lee , Jaesik Park

While portrait sketch generation is a special task in sketch synthesis, most existing methods are pixel-based, limiting their interpretability and editability. With the rise of vector generation techniques, representing sketches using…

Computer Vision and Pattern Recognition · Computer Science 2026-04-29 Yiqi Liang , Ying Liu , Dandan Long , Ruihui Li

We propose a generative framework based on generative adversarial network (GAN) to enhance facial attractiveness while preserving facial identity and high-fidelity. Given a portrait image as input, having applied gradient descent to recover…

Computer Vision and Pattern Recognition · Computer Science 2020-06-05 Yuhongze Zhou , Qinjie Xiao

In recent advances of deep generative models, face reenactment -manipulating and controlling human face, including their head movement-has drawn much attention for its wide range of applicability. Despite its strong expressiveness, it is…

Computer Vision and Pattern Recognition · Computer Science 2022-02-23 Takuya Yashima , Takuya Narihira , Tamaki Kojima

Complex, multivariable systems are often analyzed by grouping their constituent units into components, sometimes referred to as latent features, which afford physical or biological interpretation. However, a priori many different types of…

Disordered Systems and Neural Networks · Physics 2026-05-01 Philipp Fleig , Ilya Nemenman

Counterfactual image editing is an important task in generative AI, which asks how an image would look if certain features were different. The current literature on the topic focuses primarily on changing individual features while remaining…

Computer Vision and Pattern Recognition · Computer Science 2024-03-18 Yushu Pan , Elias Bareinboim

The creation of manufacturable and editable 3D shapes through Computer-Aided Design (CAD) remains a highly manual and time-consuming task, hampered by the complex topology of boundary representations of 3D solids and unintuitive design…

Computer Vision and Pattern Recognition · Computer Science 2025-04-10 Md Ferdous Alam , Faez Ahmed

Here we propose a novel model family with the objective of learning to disentangle the factors of variation in data. Our approach is based on the spike-and-slab restricted Boltzmann machine which we generalize to include higher-order…

Machine Learning · Statistics 2012-10-22 Guillaume Desjardins , Aaron Courville , Yoshua Bengio

We introduce MyStyle, a personalized deep generative prior trained with a few shots of an individual. MyStyle allows to reconstruct, enhance and edit images of a specific person, such that the output is faithful to the person's key facial…

Computer Vision and Pattern Recognition · Computer Science 2022-10-07 Yotam Nitzan , Kfir Aberman , Qiurui He , Orly Liba , Michal Yarom , Yossi Gandelsman , Inbar Mosseri , Yael Pritch , Daniel Cohen-or

We present a generative autoencoder that provides fast encoding, faithful reconstructions (eg. retaining the identity of a face), sharp generated/reconstructed samples in high resolutions, and a well-structured latent space that supports…

Machine Learning · Computer Science 2020-02-21 Ari Heljakka , Arno Solin , Juho Kannala

Deep generative models can synthesize photorealistic images of human faces with novel identities. However, a key challenge to the wide applicability of such techniques is to provide independent control over semantically meaningful…

Computer Vision and Pattern Recognition · Computer Science 2021-08-19 Marcel C. Bühler , Abhimitra Meka , Gengyan Li , Thabo Beeler , Otmar Hilliges

Understating and controlling generative models' latent space is a complex task. In this paper, we propose a novel method for learning to control any desired attribute in a pre-trained GAN's latent space, for the purpose of editing…

Computer Vision and Pattern Recognition · Computer Science 2021-11-18 Nir Diamant , Nitsan Sandor , Alex M Bronstein

Designing realistic digital humans is extremely complex. Most data-driven generative models used to simplify the creation of their underlying geometric shape do not offer control over the generation of local shape attributes. In this paper,…

Computer Vision and Pattern Recognition · Computer Science 2023-04-05 Simone Foti , Bongjin Koo , Danail Stoyanov , Matthew J. Clarkson

Self-supervised representation learning has gained increasing attention for strong generalization ability without relying on paired datasets. However, it has not been explored sufficiently for facial representation. Self-supervised facial…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Ruian He , Zhen Xing , Weimin Tan , Bo Yan

Portrait editing is a popular subject in photo manipulation. The Generative Adversarial Network (GAN) advances the generating of realistic faces and allows more face editing. In this paper, we argue about three issues in existing…

Computer Vision and Pattern Recognition · Computer Science 2019-05-27 Shuyang Gu , Jianmin Bao , Hao Yang , Dong Chen , Fang Wen , Lu Yuan

Recent deep image-to-image translation techniques allow fast generation of face images from freehand sketches. However, existing solutions tend to overfit to sketches, thus requiring professional sketches or even edge maps as input. To…

Graphics · Computer Science 2020-06-09 Shu-Yu Chen , Wanchao Su , Lin Gao , Shihong Xia , Hongbo Fu

Based on a combined data set of 4000 high resolution facial scans, we introduce a non-linear morphable face model, capable of producing multifarious face geometry of pore-level resolution, coupled with material attributes for use in…

Computer Vision and Pattern Recognition · Computer Science 2020-04-27 Ruilong Li , Karl Bladin , Yajie Zhao , Chinmay Chinara , Owen Ingraham , Pengda Xiang , Xinglei Ren , Pratusha Prasad , Bipin Kishore , Jun Xing , Hao Li

In this work we focused on GAN-based solution for the attribute guided face synthesis. Previous works exploited GANs for generation of photo-realistic face images and did not pay attention to the question of diversity of the resulting…

Computer Vision and Pattern Recognition · Computer Science 2018-06-29 Evgeny Izutov

The task of image generation started to receive some attention from artists and designers to inspire them in new creations. However, exploiting the results of deep generative models such as Generative Adversarial Networks can be long and…

Computer Vision and Pattern Recognition · Computer Science 2021-04-05 Baptiste Rozière , Morgane Riviere , Olivier Teytaud , Jérémy Rapin , Yann LeCun , Camille Couprie

Facial expression transfer and reenactment has been an important research problem given its applications in face editing, image manipulation, and fabricated videos generation. We present a novel method for image-based facial expression…

Computer Vision and Pattern Recognition · Computer Science 2019-12-16 Chao Yang , Ser-Nam Lim
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