Patents by Inventor Ruowei JIANG

Ruowei JIANG has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20250209670
    Abstract: Aspects of lighting estimation, and models therefor are provided including aspects to train such models. There is provided a lighting estimation model pre-trained using synthetic data to alleviate the costs and difficulty in obtaining real portrait image and HDR environment map paired datasets. To improve model performance, the model is training utilizing a discriminator configured to predict one or more average color values of a defined percentage of highest intensity pixels of a predicted environment map and to determine a color loss associated with the predicted environment map and the one or more average color values. The trained model can be used for a wide range of downstream tasks, including being used to generate hair renderings with realistic lighting effects for virtual try on experiences.
    Type: Application
    Filed: December 20, 2023
    Publication date: June 26, 2025
    Applicant: L'Oreal
    Inventors: Kin Ching Lydia Chau, Panagiotis-Alexandros Bokaris, Ruowei Jiang, Zhi Yu, Tao Li
  • Publication number: 20250191248
    Abstract: Aspects of hair simulation, and networks therefor are provided including aspects to train such networks. There is provided a generative model for hair simulation that is guided during training by a hair classifier model. The generative model in an embodiment is provided for use in a virtual try-on (VTO) pipeline such as for virtually trying on hair color products. Further provided is a color mapping network to process an input image and target hair color for the generative model to define the hair simulation (e.g. as an output image with simulated hair color).
    Type: Application
    Filed: December 7, 2023
    Publication date: June 12, 2025
    Applicant: L'Oreal
    Inventors: Ruowei Jiang, Zhi Yu, Sidharth Singla, Kin Ching Lydia Chau
  • Publication number: 20250111630
    Abstract: Methods, apparatus, systems achieve disentanglement in semantic editing using GANs-based models. Self-corrected (low-density) latent code samples are projected in the original latent space and the editing directions corrected though relearning based on resulting high-density and low-density regions in the amended latent space. Leveraging the original meaningful directions and semantic region-specific layers, operations interpolate the original latent codes to generate images with minority combinations of attributes, then inverts these samples back to the original latent space. In accordance with embodiments, the operations can apply to preexisting methods that learn meaningful latent directions. Attribute disentanglement is improved with small amounts of low-density region samples added.
    Type: Application
    Filed: September 29, 2023
    Publication date: April 3, 2025
    Applicant: L'Oréal
    Inventors: Zikun CHEN, Ruowei JIANG
  • Patent number: 12190637
    Abstract: There is provided methods, devices and techniques to process an image using a deep learning model to achieve continuous effect simulation by a unified network where a simple (effect class) estimator is embedded into a regular encoder-decoder architecture. The estimator allows learning of model-estimated class embeddings of all effect classes (e.g. progressive degrees of the effect), thus representing the continuous effect information without manual efforts in selecting proper anchor effect groups. In an embodiment, given a target age class, there is derived a personalized age embedding which considers two aspects of face aging: 1) a personalized residual age embedding at a model-estimated age of the subject, preserving the subject's aging information; and 2) exemplar-face aging basis at the target age, encoding the shared aging patterns among the entire population.
    Type: Grant
    Filed: December 22, 2021
    Date of Patent: January 7, 2025
    Assignee: L'Oreal
    Inventors: Zeqi Li, Ruowei Jiang, Parham Aarabi
  • Publication number: 20240362902
    Abstract: Vision Transformers (ViT) have shown their competitive advantages performance-wise compared to convolutional neural networks (CNNs) though they often come with high computational costs. Methods, systems and techniques herein learn instance-dependent attention patterns, utilizing a lightweight connectivity predictor module to estimate a connectivity score of each pair of tokens. Intuitively, two tokens have high connectivity scores if the features are considered relevant either spatially or semantically. As each token only attends to a small number of other tokens, the binarized connectivity masks are often very sparse by nature providing an opportunity to accelerate the network via sparse computations. Equipped with the learned unstructured attention pattern, sparse attention ViT produces a superior Pareto-optimal trade-off between FLOPs and top-1 accuracy on ImageNet compared to token sparsity (48%˜69% FLOPs reduction of MHSA; accuracy drop within 0.4%).
    Type: Application
    Filed: April 27, 2023
    Publication date: October 31, 2024
    Applicant: ModiFace Inc.
    Inventors: Cong WEI, Brendan DUKE, Ruowei JIANG
  • Publication number: 20240355025
    Abstract: This application provides an inter-account interaction method performed by a computer device. The method includes: displaying a battle preparation interface of a virtual battle, the battle preparation interface comprising a first icon representing a first account associated with the computer device and at least one second icon representing an account other than the first account; in response to a trigger operation on one of the at least one second icon as a target icon, displaying a prop selection area on the battle preparation interface and at least one interactive prop owned by the first account in the prop selection area; and in response to a selection of one of the at least one interactive prop as a target interactive prop, playing a target special effect animation of transmitting a special effect resource of the target interactive prop pointing from the first icon to the target icon.
    Type: Application
    Filed: July 1, 2024
    Publication date: October 24, 2024
    Inventors: Yingjie MEI, Meng WEI, Xianqi JING, Lili HAO, Xingyu XIAO, Hongjiang WANG, Ruowei JIANG, Jun ZHANG, Xiaogiang HONG, Lichao WU
  • Patent number: 12105773
    Abstract: GANs based generators are useful to perform image to image translations. GANs models have large storage sizes and resource use requirements such that they are too large to be deployed directly on mobile devices. Systems and methods define through conditioning a student GANs model having a student generator that is scaled downwardly from a teacher GANs model (and generator) using knowledge distillation. A semantic relation knowledge distillation loss is used to transfer semantic knowledge from an intermediate layer of the teacher to an intermediate layer of the student. Student generators thus defined are stored and executed by mobile devices such as smartphones and laptops to provide augmented reality experiences. Effects are simulated on images, including makeup, hair, nail and age simulation effects.
    Type: Grant
    Filed: June 29, 2021
    Date of Patent: October 1, 2024
    Assignee: L'Oreal
    Inventors: Zeqi Li, Ruowei Jiang, Parham Aarabi
  • Publication number: 20240268541
    Abstract: According to one aspect, what is proposed is a method for generating a photorealistic rendering of a cosmetic product, comprising: —obtaining (10, 12) a reference image (Xref) of a real cosmetic product (PC) applied to a first person (P1) and at least one source image (Xjsource) of a second person (P2), —implementing (13) an encoding artificial neural network (E) configured to determine characterizing parameters (E(Xref)) of the cosmetic product (PC) from the reference image (Xref), and then —implementing (14) a realistic physically based rendering engine (R) configured to generate a transformed image (R (Xjsource, E(Xref))) in which a photorealistic rendering of the cosmetic product (PC) is applied to the person (P2) from said at least one source image (Xjsource) based on the characterizing parameters (E (Xref)) of the cosmetic product (PC) that are determined by the encoding artificial neural network (E).
    Type: Application
    Filed: May 9, 2022
    Publication date: August 15, 2024
    Applicant: L'Oreal
    Inventors: Sileye Ba, Ruowei Jiang, Robin Kips
  • Publication number: 20240249504
    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.
    Type: Application
    Filed: April 5, 2024
    Publication date: July 25, 2024
    Applicant: L'Oreal
    Inventors: Zhi YU, Yuze ZHANG, Ruowei JIANG, Jeffrey HOUGHTON, Parham AARABI, Frederic Antoinin Raymond Serge FLAMENT
  • Patent number: 12029977
    Abstract: A method for generating a special effect for social networking interaction in a virtual environment of a game is performed by an electronic device. The method includes: displaying an object presentation interface of a target battle of the game when loading a virtual scene corresponding to the target battle, the object presentation interface being used for displaying a plurality of virtual objects participating in the target battle; receiving a special effect generating instruction for a first virtual object of the plurality of virtual objects, the special effect generating instruction being used for instructing to generate a special effect based on the first virtual object, and the first virtual object corresponding to a user of the electronic device triggering the special effect; and generating the special effect identifying the first virtual object in the object presentation interface.
    Type: Grant
    Filed: May 20, 2022
    Date of Patent: July 9, 2024
    Assignee: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED
    Inventors: Yingjie Mei, Zhengguo Han, Lili Hao, Xianqi Jing, Chuan Lv, Zhaoyang Li, Ruowei Jiang, Jun Zhang, Xiaoqiang Hong, Lichao Wu, Jiabin Liang, Yi Wang, Yingtong Liu, Hao Meng
  • Publication number: 20240177300
    Abstract: A method, apparatus and system according to embodiments provide image-to-image translations such as synthesis of ultraviolet (UV) images from input images in a RGB (red, green blue) color model. In an embodiment, a trained generator generates overlapping UV patch images from overlapping RBG patch images extracted from an input image. The overlapping UV patch images are blended using a Gaussian weighting factor applied to overlapping pixels having a same location in the input image. The Gaussian blending distributes weights to pixels relative to the pixel's distance to the center of its patch, with weighting being highest at the center.
    Type: Application
    Filed: November 28, 2022
    Publication date: May 30, 2024
    Applicant: L'oréal
    Inventors: Ruowei JIANG, Brendan DUKE, Parham AARABI
  • Patent number: 11978242
    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.
    Type: Grant
    Filed: June 29, 2021
    Date of Patent: May 7, 2024
    Assignee: L'Oreal
    Inventors: Zhi Yu, Yuze Zhang, Ruowei Jiang, Jeffrey Houghton, Parham Aarabi, Frederic Antoinin Raymond Serge Flament
  • Patent number: 11908128
    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.
    Type: Grant
    Filed: August 18, 2020
    Date of Patent: February 20, 2024
    Assignee: L'Oreal
    Inventors: Ruowei Jiang, Irina Kezele, Zhi Yu, Sophie Seite, Frederic Antoinin Raymond Serge Flament, Parham Aarabi, Mathieu Perrot, Julien Despois
  • Publication number: 20240037870
    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.
    Type: Application
    Filed: July 28, 2023
    Publication date: February 1, 2024
    Applicant: L'Oreal
    Inventors: Zikun CHEN, Ruowei JIANG, Brendan DUKE, Parham AARABI
  • Patent number: 11861497
    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.
    Type: Grant
    Filed: December 30, 2021
    Date of Patent: January 2, 2024
    Assignee: L'OREAL
    Inventors: Alex Levinshtein, Cheng Chang, Edmund Phung, Irina Kezele, Wenzhangzhi Guo, Eric Elmoznino, Ruowei Jiang, Parham Aarabi
  • Patent number: 11832958
    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.
    Type: Grant
    Filed: December 13, 2022
    Date of Patent: December 5, 2023
    Assignee: L'OREAL
    Inventors: Ruowei Jiang, Junwei Ma, He Ma, Eric Elmoznino, Irina Kezele, Alex Levinshtein, Julien Despois, Matthieu Perrot, Frederic Antoinin Raymond Serge Flament, Parham Aarabi
  • Publication number: 20230123037
    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.
    Type: Application
    Filed: December 13, 2022
    Publication date: April 20, 2023
    Applicant: L'OREAL
    Inventors: Ruowei JIANG, Junwei MA, He MA, Eric ELMOZNINO, Irina KEZELE, Alex LEVINSHTEIN, Julien DESPOIS, Matthieu PERROT, Frederic Antoinin Raymond Serge FLAMENT, Parham AARABI
  • Patent number: 11553872
    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.
    Type: Grant
    Filed: December 4, 2019
    Date of Patent: January 17, 2023
    Assignee: L'OREAL
    Inventors: Ruowei Jiang, Junwei Ma, He Ma, Eric Elmoznino, Irina Kezele, Alex Levinshtein, Julien Despois, Matthieu Perrot, Frederic Antoinin Raymond Serge Flament, Parham Aarabi
  • Publication number: 20220379208
    Abstract: A method for generating a special effect for social networking interaction in a virtual environment of a game is performed by an electronic device. The method includes: displaying an object presentation interface of a target battle of the game when loading a virtual scene corresponding to the target battle, the object presentation interface being used for displaying a plurality of virtual objects participating in the target battle; receiving a special effect generating instruction for a first virtual object of the plurality of virtual objects, the special effect generating instruction being used for instructing to generate a special effect based on the first virtual object, and the first virtual object corresponding to a user of the electronic device triggering the special effect; and generating the special effect identifying the first virtual object in the object presentation interface.
    Type: Application
    Filed: May 20, 2022
    Publication date: December 1, 2022
    Inventors: Yingjie MEI, Zhengguo HAN, Lili HAO, Xianqi JING, Chuan LV, Zhaoyang LI, Ruowei JIANG, Jun ZHANG, Xiaoqiang HONG, Lichao WU, Jiabin LIANG, YI WANG, Yingtong LIU, Hao MENG
  • Publication number: 20220198830
    Abstract: There is provided methods, devices and techniques to process an image using a deep learning model to achieve continuous effect simulation by a unified network where a simple (effect class) estimator is embedded into a regular encoder-decoder architecture. The estimator allows learning of model-estimated class embeddings of all effect classes (e.g. progressive degrees of the effect), thus representing the continuous effect information without manual efforts in selecting proper anchor effect groups. In an embodiment, given a target age class, there is derived a personalized age embedding which considers two aspects of face aging: 1) a personalized residual age embedding at a model-estimated age of the subject, preserving the subject's aging information; and 2) exemplar-face aging basis at the target age, encoding the shared aging patterns among the entire population.
    Type: Application
    Filed: December 22, 2021
    Publication date: June 23, 2022
    Applicant: L'Oreal
    Inventors: Zeqi LI, Ruowei Jiang, Parham Aarabi