公开(公告)号：US20220075988A1

公开(公告)日：2022-03-10

申请号：US17528294

申请日：2021-11-17

Applicant: L'Oreal

Inventor： Tian Xing LI ,  Zhi YU ,  Irina KEZELE ,  Edmund PHUNG ,  Parham AARABI

IPC: G06K9/00 ,  G06T7/143 ,  G06T7/11 ,  G06N3/04 ,  G06N3/08 ,  G06T5/20 ,  G06T19/00

Abstract: There are provided systems and methods for facial landmark detection using a convolutional neural network (CNN). The CNN comprises a first stage and a second stage where the first stage produces initial heat maps for the landmarks and initial respective locations for the landmarks. The second stage processes the heat maps and performs Region of Interest-based pooling while preserving feature alignment to produce cropped features. Finally, the second stage predicts from the cropped features a respective refinement location offset to each respective initial location. Combining each respective initial location with its respective refinement location offset provides a respective final coordinate (x,y) for each respective landmark in the image. Two-stage localization design helps to achieve fine-level alignment while remaining computationally efficient. The resulting architecture is both small enough in size and inference time to be suitable for real-time web applications such as product simulation and virtual reality.

公开(公告)号：US20230123037A1

公开(公告)日：2023-04-20

申请号：US18080331

申请日：2022-12-13

Applicant: L'OREAL

Inventor： Ruowei JIANG ,  Junwei MA ,  He MA ,  Eric ELMOZNINO ,  Irina KEZELE ,  Alex LEVINSHTEIN ,  Julien DESPOIS ,  Matthieu PERROT ,  Frederic Antoinin Raymond Serge FLAMENT ,  Parham AARABI

IPC: A61B5/00 ,  G06T7/00 ,  G06V40/16 ,  G06N3/08 ,  G06N3/045

Abstract: There is shown and described a deep learning based system and method for skin diagnostics as well as testing metrics that show that such a deep learning based system outperforms human experts on the task of apparent skin diagnostics. Also shown and described is a system and method of monitoring a skin treatment regime using a deep learning based system and method for skin diagnostics.

公开(公告)号：US20210406996A1

公开(公告)日：2021-12-30

申请号：US17361743

申请日：2021-06-29

Applicant: L'Oreal

Inventor： Zhi YU ,  Yuze ZHANG ,  Ruowei JIANG ,  Jeffrey HOUGHTON ,  Parham AARABI ,  Frederic FLAMENT

IPC: G06Q30/06 ,  G06N3/04 ,  G06K9/00 ,  G06K9/62

Abstract: There is described a deep learning supervised regression based model including methods and systems for facial attribute prediction and use thereof. An example of use is an augmented and/or virtual reality interface to provide a modified image responsive to facial attribute predictions determined from the image. Facial effects matching facial attributes are selected to be applied in the interface

公开(公告)号：US20200342630A1

公开(公告)日：2020-10-29

申请号：US16854975

申请日：2020-04-22

Applicant: L'Oreal

Inventor： Eric ELMOZNINO ,  Parham AARABI ,  Yuze ZHANG

IPC: G06T7/90 ,  G06T11/00 ,  G06Q30/06 ,  G06N3/08

Abstract: Provided are systems and methods to perform colour extraction from swatch images and to define new images using extracted colours. Source images may be classified using a deep learning net (e.g. a CNN) to indicate colour representation strength and drive colour extraction. A clustering classifier is trained to use feature vectors extracted by the net. Separately, pixel clustering is useful when extracting the colour. Cluster count can vary according to classification. In another manner, heuristics (with or without classification) are useful when extracting. Resultant clusters are evaluated against a set of (ordered) expected colours to determine a match. Instances of standardized swatch images may be defined from a template swatch image and respective extracted colours using image processing. The extracted colour may be presented in an augmented reality GUI such as a virtual try-on application and applied to a user image such as a selfie using image processing.

公开(公告)号：US20200160153A1

公开(公告)日：2020-05-21

申请号：US16683398

申请日：2019-11-14

Applicant: L'Oreal

Inventor： Eric ELMOZNINO ,  He MA ,  Irina KEZELE ,  Edmund PHUNG ,  Alex LEVINSHTEIN ,  Parham AARABI

IPC: G06N3/04 ,  G06T19/00 ,  G06N20/00 ,  G06N3/08 ,  G06F3/01

Abstract: Systems and methods relate to a network model to apply an effect to an image such as an augmented reality effect (e.g. makeup, hair, nail, etc.). The network model uses a conditional cycle-consistent generative image-to-image translation model to translate images from a first domain space where the effect is not applied and to a second continuous domain space where the effect is applied. In order to render arbitrary effects (e.g. lipsticks) not seen at training time, the effect's space is represented as a continuous domain (e.g. a conditional variable vector) learned by encoding simple swatch images of the effect, such as are available as product swatches, as well as a null effect. The model is trained end-to-end in an unsupervised fashion. To condition a generator of the model, convolutional conditional batch normalization (CCBN) is used to apply the vector encoding the reference swatch images that represent the makeup properties.

公开(公告)号：US20240249504A1

公开(公告)日：2024-07-25

申请号：US18627827

申请日：2024-04-05

Applicant: L'Oreal

Inventor： Zhi YU ,  Yuze ZHANG ,  Ruowei JIANG ,  Jeffrey HOUGHTON ,  Parham AARABI ,  Frederic Antoinin Raymond Serge FLAMENT

IPC: G06V10/764 ,  G06N3/04 ,  G06Q30/0601 ,  G06V10/82 ,  G06V40/16

CPC classification number: G06V10/764 ,  G06N3/04 ,  G06Q30/0631 ,  G06Q30/0643 ,  G06V10/82 ,  G06V40/162 ,  G06V40/168 ,  G06V40/171 ,  G06V40/172

Abstract: There is described a deep learning supervised regression based model including methods and systems for facial attribute prediction and use thereof. An example of use is an augmented and/or virtual reality interface to provide a modified image responsive to facial attribute predictions determined from the image. Facial effects matching facial attributes are selected to be applied in the interface.

公开(公告)号：US20230169571A1

公开(公告)日：2023-06-01

申请号：US18102139

申请日：2023-01-27

Applicant: L'OREAL

Inventor： Eric ELMOZNINO ,  Irina KEZELE ,  Parham AARABI

IPC: G06Q30/0601 ,  G06T5/50 ,  G06N20/00 ,  G06F18/214 ,  G06V10/764 ,  G06V10/774 ,  G06V10/778

CPC classification number: G06Q30/0631 ,  G06T5/50 ,  G06N20/00 ,  G06F18/214 ,  G06V10/764 ,  G06V10/774 ,  G06V10/7788

Abstract: Techniques are provided for computing systems, methods and computer program products to produce efficient image-to-image translation by adapting unpaired datasets for supervised learning. A first model (a powerful model) may be defined and conditioned using unsupervised learning to produce a synthetic paired dataset from the unpaired dataset, translating images from a first domain to a second domain and images from the second domain to the first domain. The synthetic data generated is useful as ground truths in supervised learning. The first model may be conditioned to overfit the unpaired dataset to enhance the quality of the paired dataset (e.g. the synthetic data generated). A run-time model such as for a target device is trained using the synthetic paired dataset and supervised learning. The run-time model is small and fast to meet the processing resources of the target device (e.g. a personal user device such as a smart phone, tablet, etc.)

公开(公告)号：US20220351416A1

公开(公告)日：2022-11-03

申请号：US17869942

申请日：2022-07-21

Applicant: L'Oreal

Inventor： Eric ELMOZNINO ,  Parham AARABI ,  Yuze ZHANG

IPC: G06T7/90 ,  G06N3/08 ,  G06Q30/06 ,  G06T11/00

Abstract: Provided are systems and methods to perform colour extraction from swatch images and to define new images using extracted colours. Source images may be classified using a deep learning net (e.g. a CNN) to indicate colour representation strength and drive colour extraction. A clustering classifier is trained to use feature vectors extracted by the net. Separately, pixel clustering is useful when extracting the colour. Cluster count can vary according to classification. In another manner, heuristics (with or without classification) are useful when extracting. Resultant clusters are evaluated against a set of (ordered) expected colours to determine a match. Instances of standardized swatch images may be defined from a template swatch image and respective extracted colours using image processing. The extracted colour may be presented in an augmented reality GUI such as a virtual try-on application and applied to a user image such as a selfie using image processing.

公开(公告)号：US20200027744A1

公开(公告)日：2020-01-23

申请号：US16588723

申请日：2019-09-30

Applicant: L'Oreal

Inventor： Parham AARABI

IPC: H01L21/308 ,  H01L21/268 ,  G03F7/20 ,  G03F1/50

Abstract: A computer-implemented method for correcting a makeup or skin effect to be rendered on a surface region of an image of a portion of a body of a person. The method and system correcting the makeup or skin effect by accounting for image-specific light field parameters, such as a light profile estimate and minimum light field estimation, and rendering the corrected the makeup or skin effect on the image to generate a corrected image.

公开(公告)号：US20240037870A1

公开(公告)日：2024-02-01

申请号：US18227546

申请日：2023-07-28

Applicant: L'Oreal

Inventor： Zikun CHEN ,  Ruowei JIANG ,  Brendan DUKE ,  Parham AARABI

IPC: G06T19/00

CPC classification number: G06T19/006

Abstract: Methods, apparatus and techniques herein relates to determining directions in GAN latent space and obtaining disentangled controls over GAN output semantics, for example, to enable use of such to generating synthesized images such as for use to train another model or create an augmented reality The methods, apparatus and techniques herein, in accordance with embodiments, utilize the gradient directions of auxiliary networks to control semantics in GAN latent codes. It is shown that minimal amounts of labelled data with sizes as small as 60 samples can be used, which data can be obtained quickly with human supervision. It is also shown herein, in accordance with embodiments, to select important latent code channels with masks during manipulation, resulting in more disentangled controls.