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公开(公告)号：US20220116549A1
公开(公告)日：2022-04-14
申请号：US17067781
申请日：2020-10-12
Applicant: Microsoft Technology Licensing, LLC
Inventor： Alexandros NEOFYTOU , Eric Chris Wolfgang SOMMERLADE , Alejandro SZTRAJMAN , Sunando SENGUPTA
Abstract: Technology is described herein that uses an object-encoding system to convert an object image into a combined encoding. The object image depicts a reference object, while the combined encoding represents an environment image. The environment image, in turn, depicts an estimate of an environment that has produced the illumination effects exhibited by the reference object. The combined encoding includes: a first part that represents image content in the environment image within a high range of intensities values; and a second part that represents image content within a low range of intensity values. Also described herein is a training system that trains the object-encoding system based on combined encodings produced by a separately-trained environment-encoding system. Also described herein are various applications of the object-encoding system and environment-encoding system.
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2.发明公开公开(公告)号：US20240331094A1
公开(公告)日：2024-10-03
申请号：US18188050
申请日：2023-03-22
Applicant: Microsoft Technology Licensing, LLC
Inventor： Samira POUYANFAR , Sunando SENGUPTA , Eric Chris Wolfgang SOMMERLADE , Anjali S. PARIKH , Ebey Paulose ABRAHAM , Brian Timothy HAWKINS , Mahmoud MOHAMMADI
CPC classification number: G06T5/50 , G06T5/70 , G06T5/73 , G06T7/194 , G06V40/167 , G06T2207/20081
Abstract: The present disclosure relates to an image restoration system that efficiently and accurately produces high-quality images captured under low-light and/or low-quality environmental conditions. To illustrate, when a user is in a low-lit environment and participating in a video stream, the image restoration system enhances the quality of the image by dynamically re-lighting the user's face. Moreover, it significantly enhances the image quality to the extent that other users viewing the video stream are unaware of the poor environmental conditions of the user. In addition, the image restoration system creates and utilizes an image restoration machine-learning model to improve the quality of low-quality images by re-lighting and restoring them in real time. Various implementations combine an autoencoder model with a distortion classifier model to create the image restoration machine-learning model.
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公开(公告)号：US20220383034A1
公开(公告)日：2022-12-01
申请号：US17331876
申请日：2021-05-27
Applicant: Microsoft Technology Licensing, LLC
Abstract: A method of improving image quality of a stream of input images is described. The stream of input images, including a current input image, is received. One or more target objects, including a first target object, are identified spatio-temporally within the stream of input images. The one or more target objects are tracked spatio-temporally within the stream of input images. The current input image is segmented into i) a foreground including the first target object, and ii) a background. The foreground is processed to have improved image quality in the current input image. Processing of the foreground further comprises processing the first target object using a same processing technique as for a prior input image of the stream of input images based on the tracking of the first target object. The background is processed differently from the foreground. An output image is generated by merging the foreground with the background.
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公开(公告)号：US20230289919A1
公开(公告)日：2023-09-14
申请号：US17693056
申请日：2022-03-11
Applicant: Microsoft Technology Licensing, LLC
Inventor： Sunando SENGUPTA , John G A WEISS , Luming LIANG , Ilya D. ZHARKOV , Eric CW SOMMERLADE
CPC classification number: G06T3/40 , G06V10/25 , G06T7/246 , G06T2207/20081
Abstract: Aspects of the present disclosure relate to video stream refinement for a dynamic scene. In examples, a system is provided that includes at least one processor, and memory storing instructions that, when executed by the at least one processor, causes the system to perform a set of operations. The set of operations include receiving an input video stream, identifying, within the input video stream, a frame portion containing features of interest, enlarging the frame portion containing the features of interest, enhancing the frame portion of the input video stream to increase fidelity within the frame portion, and displaying the enhanced frame portion.
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公开(公告)号：US20220400228A1
公开(公告)日：2022-12-15
申请号：US17342849
申请日：2021-06-09
Applicant: Microsoft Technology Licensing, LLC
Abstract: Methods and systems for applying gaze adjustment techniques to participants in a video conference are disclosed. Some examples may include: receiving, at computing system, image adjustment information associated with a video stream including images of a first participant, identifying, for a display layout of a communication application, a location displaying the images of the first participant, determining, based on the received image adjustment information, a location displaying images of a second participant for the display layout, the received image adjustment information indicating that an eye gaze of the first participant being directed toward the second participant, computing an eye gaze direction of the first participant based on the location displaying images of the second participant, generating gaze-adjusted images based on the desired eye gaze direction of the first participant and replacing the images within the video stream with the gaze-adjusted images.
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Patent Agency Ranking
公开(公告)号：US20210216817A1
公开(公告)日：2021-07-15
申请号：US16844930
申请日：2020-04-09
Applicant: Microsoft Technology Licensing, LLC
Inventor： Eric Chris Wolfgang SOMMERLADE , Yang LIU , Alexandros NEOFYTOU , Sunando SENGUPTA
Abstract: A computing system includes an encoder that receives an input image and encodes the input image into real image features, a decoder that decodes the real image features into a reconstructed image, a generator that receives first audio data corresponding to the input image and generates first synthetic image features from the first audio data, and receives second audio data and generates second synthetic image features from the second audio data, a discriminator that receives both the real and synthetic image features and determines whether a target feature is real or synthetic, and a classifier that classifies a scene of the second audio data based on the second synthetic image features.
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公开(公告)号：US20240054683A1
公开(公告)日：2024-02-15
申请号：US18383956
申请日：2023-10-26
Applicant: Microsoft Technology Licensing, LLC
Inventor： Sunando SENGUPTA , Alexandros NEOFYTOU , Eric Chris Wolfgang SOMMERLADE , Yang LIU
IPC: G06T9/00 , G06T3/60 , G10L19/012 , G10L25/51 , G06F18/21
CPC classification number: G06T9/00 , G06T3/60 , G10L19/012 , G10L25/51 , G06F18/21 , G10L2019/0002
Abstract: In various embodiments, a computer-implemented method of training a neural network for creating an output signal of different modality from an input signal is described. In embodiments, the first modality may be a sound signal or a visual image and where the output signal would be a visual image or a sound signal, respectively. In embodiments a model is trained using a first pair of visual and audio networks to train a set of codebooks using known visual signals and the audio signals and using a second pair of visual and audio networks to further train the set of codebooks using the augmented visual signals and the augmented audio signals. Further, the first and the second visual networks are equally weighted and where the first and the second audio networks are equally weighted.
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公开(公告)号：US20230206406A1
公开(公告)日：2023-06-29
申请号：US18116052
申请日：2023-03-01
Applicant: Microsoft Technology Licensing, LLC
Inventor： Alexandros NEOFYTOU , Eric Chris Wolfgang SOMMERLADE , Sunando SENGUPTA , Yang LIU
IPC: G06T5/00 , G06N3/08 , G06F18/214
CPC classification number: G06T5/005 , G06N3/08 , G06F18/214 , G06T2207/20081 , G06T2207/20084
Abstract: In various embodiments, a computer-implemented method of training a neural network for relighting an image is described. A first training set that includes source images and a target illumination embedding is generated, the source images having respective illuminated subjects. A second training set that includes augmented images and the target illumination embedding is generated, where the augmented images corresponding to the source images. A first autoencoder is trained using the first training set to generate a first output set that includes estimated source illumination embeddings and first reconstructed images that correspond to the source images, the reconstructed images having respective subjects that are i) from the corresponding source image, and ii) illuminated based on the target illumination embedding. A second autoencoder is trained using the second training set to generate a second output set that includes estimated augmented illumination embeddings and second reconstructed images that correspond to the augmented images.
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公开(公告)号：US20210097644A1
公开(公告)日：2021-04-01
申请号：US16696639
申请日：2019-11-26
Applicant: Microsoft Technology Licensing, LLC
Abstract: A method for image enhancement on a computing device includes receiving a digital input image depicting a human eye. From the digital input image, the computing device generates a gaze-adjusted image via a gaze adjustment machine learning model by changing an apparent gaze direction of the human eye. From the gaze-adjusted image and potentially in conjunction with the digital input image, the computing device generates a detail-enhanced image via a detail enhancement machine learning model by adding or modifying details. The computing device outputs the detail-enhanced image.
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公开(公告)号：US20240071042A1
公开(公告)日：2024-02-29
申请号：US17899325
申请日：2022-08-30
Applicant: Microsoft Technology Licensing, LLC
Inventor： Sunando SENGUPTA , Ebey Paulose ABRAHAM , Alexandros NEOFYTOU , Eric Chris Wolfgang SOMMERLADE
CPC classification number: G06V10/60 , G06T5/50 , G06V10/141 , G06V10/25 , G06V10/7715 , G06V40/169 , H04N7/15 , G06T2207/10016 , G06T2207/10024 , G06T2207/10152 , G06T2207/20081 , G06T2207/20221
Abstract: An image-processing technique is described herein for removing a visual effect in a face region of an image caused, at least in part, by screen illumination provided by an electronic screen. The technique can perform this removal without advance knowledge of the nature of the screen illumination provided by the electronic screen. The technique improves the quality of the image and also protects the privacy of a user by removing the visual effect in the face region that may reveal the characteristics of display information presented on the electronic screen. In some implementations, the technique first adjusts a face region of the image, and then adjusts other regions in the image for consistency with the face region. In some implementations, the technique is applied by a videoconferencing application, and is performed by a local computing device.
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