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：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：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.

公开(公告)号：US20210012493A1

公开(公告)日：2021-01-14

申请号：US16996087

申请日：2020-08-18

Applicant: L'Oreal

Inventor： Ruowei JIANG ,  Irina KEZELE ,  Zhi Yu ,  Sophie SEITE ,  Frederic FLAMENT ,  Parham AARABI

IPC: G06T7/00 ,  G16H50/20 ,  G06Q30/06 ,  A61B5/00

Abstract: Systems and methods process images to determine a skin condition severity analysis and to visualize a skin analysis such as using a deep neural network (e.g. a convolutional neural network) where a problem was formulated as a regression task with integer-only labels. Auxiliary classification tasks (for example, comprising gender and ethnicity predictions) are introduced to improve performance. Scoring and other image processing techniques may be used (e.g. in assoc. with the model) to visualize results such as highlighting the analyzed image. It is demonstrated that the visualization of results, which highlight skin condition affected areas, can also provide perspicuous explanations for the model. A plurality (k) of data augmentations may be made to a source image to yield k augmented images for processing. Activation masks (e.g. heatmaps) produced from processing the k augmented images are used to define a final map to visualize the skin analysis.

公开(公告)号：US20200320748A1

公开(公告)日：2020-10-08

申请号：US16753214

申请日：2018-10-24

Applicant: L'OREAL

Inventor： Alex LEVINSHTEIN ,  Cheng CHANG ,  Edmund PHUNG ,  Irina KEZELE ,  Wenzhangzhi GUO ,  Eric ELMOZNINO ,  Ruowei JIANG ,  Parham AARABI

IPC: G06T11/00 ,  G06T7/90 ,  G06T1/20 ,  G06T7/11 ,  G06K9/62 ,  G06K9/46 ,  G06K9/00 ,  G06N3/08

Abstract: A system and method implement deep learning on a mobile device to provide a convolutional neural network (CNN) for real time processing of video, for example, to color hair. Images are processed using the CNN to define a respective hair matte of hair pixels. The respective object mattes may be used to determine which pixels to adjust when adjusting pixel values such as to change color, lighting, texture, etc. The CNN may comprise a (pre-trained) network for image classification adapted to produce the segmentation mask. The CNN may be trained for image segmentation (e.g. using coarse segmentation data) to minimize a mask-image gradient consistency loss. The CNN may further use skip connections between corresponding layers of an encoder stage and a decoder stage where shallower layers in the encoder, which contain high-res but weak features are combined with low resolution but powerful features from deeper decoder layers.