公开(公告)号：US12198229B2

公开(公告)日：2025-01-14

申请号：US17782727

申请日：2020-01-08

Applicant: GOOGLE LLC

Inventor： Xiyang Luo ,  Innfarn Yoo ,  Feng Yang

IPC: G06T11/00 ,  G06T7/90 ,  G06T9/00 ,  G06V10/28 ,  G06V10/56 ,  G06V10/74 ,  G06V10/82

Abstract: Example embodiments allow for training of encoders (e.g., artificial neural networks (ANNs)) to generate a color palette based on an input image. The color palette can then be used to generate, using the input image, a quantized, reduced color depth image that corresponds to the input image. Differences between a plurality of such input images and corresponding quantized images are used to train the encoder. Encoders trained in this manner are especially suited for generating color palettes used to convert images into different reduced color depth image file formats. Such an encoder also has benefits, with respect to memory use and computational time or cost, relative to the median-cut algorithm or other methods for producing reduced color depth color palettes for images.

公开(公告)号：US20230325959A1

公开(公告)日：2023-10-12

申请号：US17926213

申请日：2021-06-21

Applicant: Google LLC

Inventor： Dake He ,  Tianhao Zhang ,  Elnaz Barshan Tashnizi ,  Xiyang Luo ,  Huiwen Chang ,  Feng Yang ,  Ryan Matthew Haggarty

IPC: G06T1/00 ,  G06T3/40 ,  G06T5/20 ,  G06V10/764

CPC classification number: G06T1/0021 ,  G06T3/40 ,  G06T5/20 ,  G06V10/764 ,  G06T2201/0065 ,  G06T2207/20081

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for detecting and decoding a visually imperceptible or perceptible watermark. A watermark detection apparatus determines whether the particular image includes a visually imperceptible or perceptible watermark using detector a machine learning model. If the watermark detection apparatus detects a watermark, the particular image is routed to a watermark decoder. If the watermark detection apparatus cannot detect a watermark in the particular image, the particular image is filtered from further processing. The watermark decoder decodes the visually imperceptible or perceptible watermark detected in the particular image. After decoding, an item depicted in the particular image is validated based data extracted from the decoded visually imperceptible or perceptible watermark.

公开(公告)号：US20230111326A1

公开(公告)日：2023-04-13

申请号：US17792062

申请日：2020-01-13

Applicant: GOOGLE LLC

Inventor： Ruohan Zhan ,  Feng Yang ,  Xiyang Luo ,  Peyman Milanfar ,  Huiwen Chang ,  Ce Liu

IPC: G06T1/00 ,  G06T9/00 ,  G06V10/75 ,  G06V10/82

Abstract: Methods, systems, and computer programs encoded on a computer storage medium, that relate to extracting digital watermarks from images, irrespective of distortions introduced into these images. Methods can include inputting a first data item into a channel encoder that can generate a first encoded data item that is greater in length than the first data item and that (1) includes the input data item and (2) new data this is redundant of the input data item. Based on the first encoded data item and a first image, an encoder model can generate a first encoded image into which the first encoded data is embedded as a digital watermark. A decoder model can decode the first encoded data item to generate a second data, which can be decoded by the channel decoder to generate data that is predicted to be the first data.

公开(公告)号：US11429894B2

公开(公告)日：2022-08-30

申请号：US16288217

申请日：2019-02-28

Applicant: Google LLC

Inventor： Elad Edwin Tzvi Eban ,  Alan Mackey ,  Xiyang Luo

IPC: G06N20/00

Abstract: Example aspects of the present disclosure are directed to systems and methods for learning classification models which satisfy constraints such as, for example, constraints that can be expressed as a predicted positive rate or negative rate on a subset of the training dataset. In particular, through the use of quantile estimators, the systems and methods of the present disclosure can transform a constrained optimization problem into an unconstrained optimization problem that is solved more efficiently and generally than the constrained optimization problem. As one example, the unconstrained optimization problem can include optimizing an objective function where a decision threshold of the classification model is expressed as an estimator of a quantile function on the classification scores of the machine-learned classification model for a subset of the training dataset at a desired quantile.

公开(公告)号：US12238322B2

公开(公告)日：2025-02-25

申请号：US18008789

申请日：2022-01-11

Applicant: GOOGLE LLC

Inventor： Xiyang Luo ,  Feng Yang ,  Elnaz Barshan Tashnizi ,  Dake He ,  Ryan Matthew Haggarty ,  Michael Gene Goebel

IPC: H04N19/467 ,  G06T1/00

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for jointly training an encoder that generates a watermark and a decoder that decodes a data item encoded within the watermark. The training comprises obtaining a plurality of training images and data items. For each training image, a first watermark is generated using an encoder and a subsequent second watermark is generated by tiling two or more first watermarks. The training image is watermarked using the second watermark to generate a first error value and distortions are added to the watermarked image. A distortion detector predicts the distortions based on which the distorted image is modified. The modified image is decoded by the decoder to generate a predicted data item and a second error value. The training parameters of the encoder and decoder are adjusted based on the first and the second error value.

公开(公告)号：US20230362399A1

公开(公告)日：2023-11-09

申请号：US18008789

申请日：2022-01-11

Applicant: GOOGLE LLC

Inventor： Xiyang Luo ,  Feng Yang ,  Elnaz Barshan Tashnizi ,  Dake He ,  Ryan Matthew Haggarty ,  Michael Gene Goebel

IPC: H04N19/467 ,  G06T1/00

CPC classification number: H04N19/467 ,  G06T1/0021

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for jointly training an encoder that generates a watermark and a decoder that decodes a data item encoded within the watermark. The training comprises obtaining a plurality of training images and data items. For each training image, a first watermark is generated using an encoder and a subsequent second watermark is generated by tiling two or more first watermarks. The training image is watermarked using the second watermark to generate a first error value and distortions are added to the watermarked image. A distortion detector predicts the distortions based on which the distorted image is modified. The modified image is decoded by the decoder to generate a predicted data item and a second error value. The training parameters of the encoder and decoder are adjusted based on the first and the second error value.

公开(公告)号：US20220358537A1

公开(公告)日：2022-11-10

申请号：US17760535

申请日：2020-08-06

Applicant: Google LLC

Inventor： Catherine Shyu ,  Luying Li ,  Feng Yang ,  Junjie Ke ,  Xiyang Luo ,  Hao Feng ,  Chao-Hung Chen ,  Wenjing Kang ,  Zheng Xia ,  Shun-Chuan Chen ,  Yicong Tian ,  Xia Li ,  Han Ke

IPC: G06Q30/02

Abstract: Systems, devices, methods, and computer readable medium for evaluating visual quality of digital content are disclosed. Methods can include identifying content assets including one or more images that are combined to create different digital components distributed to one or more client devices. A quality of each of the one or more images is evaluated using one or more machine learning models trained to evaluate one or more visual aspects that are deemed indicative of visual quality. An aggregate quality for the content assets is determined based, at least in part, on an output of the one or more machine learning models indicating the visual quality of each of the one or more images. A graphical user interface of a first computing device is updated to present a visual indication of the aggregate quality of the content assets.

公开(公告)号：US20190266513A1

公开(公告)日：2019-08-29

申请号：US16288217

申请日：2019-02-28

Applicant: Google LLC

Inventor： Elad Edwin Tzvi Eban ,  Alan Mackey ,  Xiyang Luo

IPC: G06N20/00

Abstract: Example aspects of the present disclosure are directed to systems and methods for learning classification models which satisfy constraints such as, for example, constraints that can be expressed as a predicted positive rate or negative rate on a subset of the training dataset. In particular, through the use of quantile estimators, the systems and methods of the present disclosure can transform a constrained optimization problem into an unconstrained optimization problem that is solved more efficiently and generally than the constrained optimization problem. As one example, the unconstrained optimization problem can include optimizing an objective function where a decision threshold of the classification model is expressed as an estimator of a quantile function on the classification scores of the machine-learned classification model for a subset of the training dataset at a desired quantile.

公开(公告)号：US20240087075A1

公开(公告)日：2024-03-14

申请号：US18027418

申请日：2022-01-11

Applicant: Google LLC

Inventor： Xiyang Luo ,  Feng Yang ,  Elnaz Barshan Tashnizi ,  Dake He ,  Ryan Matthew Haggarty ,  Michael Gene Goebel

IPC: G06T1/00 ,  G06T3/40 ,  G06T7/00 ,  G06T7/11

CPC classification number: G06T1/0028 ,  G06T3/4046 ,  G06T7/0002 ,  G06T7/11 ,  G06T2201/0202 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30168

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating and decoding watermarks. An image and a data item is received. The encoder generates a first watermark and then a second watermark is generated using multiple first watermarks. The second watermark is used to watermark the image by overlaying the second watermark over the image. To decode the watermark, presence of a watermark is determined on a portion of an image. A distortion model determines distortions in the image and modifies the portion of the image based on the predicted distortions. The modified portion is decoded using the decoder to obtain a predicted first data item that is further used to validate the watermark based on the first data item.

公开(公告)号：US20230130410A1

公开(公告)日：2023-04-27

申请号：US17918170

申请日：2020-04-17

Applicant: Google LLC

Inventor： Xiyang Luo ,  Feng Yang ,  Hossein Talebi

IPC: G06T9/00 ,  G06T3/40

Abstract: Methods, systems, and computer programs encoded on a computer storage medium, that relate to generating quantization tables that are used during digital image compression of a digital image. Multiple training images are obtained. A model can be trained using the training images to generate a quantization table that can be used during encoding of an input image. For each training image, a quantization table can be obtained using the model. Using the quantization table, an encoded digital image is obtained for the training image. Using the encoded digital image and the training image, an image quality loss and a compression loss can be determined. An overall loss of the model can be determined by combining the image quality loss and the compression loss for the training image. The model can be updated based on the overall loss.