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公开(公告)号：US12086913B2
公开(公告)日：2024-09-10
申请号：US17961388
申请日：2022-10-06
Applicant: Google LLC
Inventor： Mikaël Bonnevie , Yuanzhen Li , Ce Liu
CPC classification number: G06T11/60 , G06T3/40 , G06T5/70 , G06T7/194 , G06T2200/24
Abstract: A multimedia communication system and computer-implemented method for transmitting auxiliary display content to an end-user communication device to be rendered on a display device with a special effect to emphasize an image included in the auxiliary display content, comprising a processor and a transmitter. The processor can be arranged to analyze image data included in an auxiliary display content, detect an object image or a background image in the auxiliary display content based on the analysis of the image data, determine a special effect based on the analysis of the image data, and apply the special effect to the auxiliary display content to modify display properties for the auxiliary display content such that the object image is emphasized or pops-out. The transmitter can be arranged to send the auxiliary display content with modified display properties to an end-user communication device. The special effect can comprise a non-customization special effect, a simple foreground special effect or a selective foreground special effect.
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公开(公告)号：US11526996B2
公开(公告)日：2022-12-13
申请号：US17055831
申请日：2019-06-20
Applicant: GOOGLE LLC
Inventor： Michael Rubinstein , Derek Debusschere , Mike Krainin , Ce Liu
Abstract: Example embodiments allow for fast, efficient motion-magnification of video streams by decomposing image frames of the video stream into local phase information at multiple spatial scales and/or orientations. The phase information for each image frame is then scaled to magnify local motion and the scaled phase information is transformed back into image frames to generate a motion-magnified video stream. Scaling of the phase information can include temporal filtering of the phase information across image frames, for example, to magnify motion at a particular frequency. In some embodiments, temporal filtering of phase information at a frequency of breathing, cardiovascular pulse, or some other process of interest allows for motion-magnification of motions within the video stream corresponding to the breathing or the other particular process of interest. The phase information can also be used to determine time-varying motion signals corresponding to motions of interest within the video stream.
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公开(公告)号：US20220036613A1
公开(公告)日：2022-02-03
申请号：US17009194
申请日：2020-09-01
Applicant: Google LLC
Inventor： Mikaël Bonnevie , Yuanzhen Li , Ce Liu
Abstract: A multimedia communication system and computer-implemented method for transmitting auxiliary display content to an end-user communication device to be rendered on a display device with a special effect to emphasize an image included in the auxiliary display content, comprising a processor and a transmitter. The processor can be arranged to analyze image data included in an auxiliary display content, detect an object image or a background image in the auxiliary display content based on the analysis of the image data, determine a special effect based on the analysis of the image data, and apply the special effect to the auxiliary display content to modify display properties for the auxiliary display content such that the object image is emphasized or pops-out. The transmitter can be arranged to send the auxiliary display content with modified display properties to an end-user communication device. The special effect can comprise a non-customization special effect, a simple foreground special effect or a selective foreground special effect.
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4.发明申请公开(公告)号：US20210090279A1
公开(公告)日：2021-03-25
申请号：US16578215
申请日：2019-09-20
Applicant: Google LLC
Inventor： Tali Dekel , Forrester Cole , Ce Liu , William Freeman , Richard Tucker , Noah Snavely , Zhengqi Li
Abstract: A method includes obtaining a reference image and a target image each representing an environment containing moving features and static features. The method also includes determining an object mask configured to mask out the moving features and preserves the static features in the target image. The method additionally includes determining, based on motion parallax between the reference image and the target image, a static depth image representing depth values of the static features in the target image. The method further includes generating, by way of a machine learning model, a dynamic depth image representing depth values of both the static features and the moving features in the target image. The model is trained to generate the dynamic depth image by determining depth values of at least the moving features based on the target image, the object mask, and the static depth image.
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公开(公告)号：US12190403B2
公开(公告)日：2025-01-07
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
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.
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Patent Agency Ranking
6.发明授权公开(公告)号：US11978225B2
公开(公告)日：2024-05-07
申请号：US18135678
申请日：2023-04-17
Applicant: Google LLC
Inventor： Tali Dekel , Forrester Cole , Ce Liu , William Freeman , Richard Tucker , Noah Snavely , Zhengqi Li
CPC classification number: G06T7/579 , G06T7/246 , G06T7/73 , G06T2207/10016 , G06T2207/10028 , G06T2207/20081 , G06T2207/30244
Abstract: A method includes obtaining a reference image and a target image each representing an environment containing moving features and static features. The method also includes determining an object mask configured to mask out the moving features and preserves the static features in the target image. The method additionally includes determining, based on motion parallax between the reference image and the target image, a static depth image representing depth values of the static features in the target image. The method further includes generating, by way of a machine learning model, a dynamic depth image representing depth values of both the static features and the moving features in the target image. The model is trained to generate the dynamic depth image by determining depth values of at least the moving features based on the target image, the object mask, and the static depth image.
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公开(公告)号：US20240022760A1
公开(公告)日：2024-01-18
申请号：US18256837
申请日：2021-08-05
Applicant: Google LLC
Inventor： Yinxiao Li , Peyman Milanfar , Feng Yang , Ce Liu , Ming-Hsuan Yang , Pengchong Jin
IPC: H04N19/59 , G06T3/00 , H04N19/117 , G06V10/74 , H04N19/503 , H04N19/70 , H04N19/80
CPC classification number: H04N19/59 , G06T3/0093 , H04N19/117 , G06V10/761 , H04N19/503 , H04N19/70 , H04N19/80
Abstract: Example aspects of the present disclosure are directed to systems and methods which feature a machine-learned video super-resolution (VSR) model which has been trained using a bi-directional training approach. In particular, the present disclosure provides a compression-informed (e.g., compression-aware) super-resolution model that can perform well on real-world videos with different levels of compression. Specifically, example models described herein can include three modules to robustly restore the missing information caused by video compression. First, a bi-directional recurrent module can be used to reduce the accumulated warping error from the random locations of the intra-frame from compressed video frames. Second, a detail-aware flow estimation module can be added to enable recovery of high resolution (HR) flow from compressed low resolution (LR) frames. Finally, a Laplacian enhancement module can add high-frequency information to the warped HR frames washed out by video encoding.
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公开(公告)号：US20230153629A1
公开(公告)日：2023-05-18
申请号：US17920623
申请日：2021-04-12
Applicant: Google LLC
Inventor： Dilip Krishnan , Prannay Khosla , Piotr Teterwak , Aaron Yehuda Sarna , Aaron Joseph Maschinot , Ce Liu , Philip John Isola , Yonglong Tian , Chen Wang
IPC: G06N3/09 , G06V10/74 , G06V10/776 , G06V10/82
CPC classification number: G06N3/09 , G06V10/761 , G06V10/776 , G06V10/82
Abstract: The present disclosure provides an improved training methodology that enables supervised contrastive learning to be simultaneously performed across multiple positive and negative training examples. In particular, example aspects of the present disclosure are directed to an improved, supervised version of the batch contrastive loss, which has been shown to be very effective at learning powerful representations in the self-supervised setting Thus, the proposed techniques adapt contrastive learning to the fully supervised setting and also enable learning to occur simultaneously across multiple positive examples.
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公开(公告)号：US20210326660A1
公开(公告)日：2021-10-21
申请号：US17235992
申请日：2021-04-21
Applicant: Google LLC
Inventor： Dilip Krishnan , Prannay Khosla , Piotr Teterwak , Aaron Yehuda Sarna , Aaron Joseph Maschinot , Ce Liu , Phillip John Isola , Yonglong Tian , Chen Wang
Abstract: The present disclosure provides an improved training methodology that enables supervised contrastive learning to be simultaneously performed across multiple positive and negative training examples. In particular, example aspects of the present disclosure are directed to an improved, supervised version of the batch contrastive loss, which has been shown to be very effective at learning powerful representations in the self-supervised setting. Thus, the proposed techniques adapt contrastive learning to the fully supervised setting and also enable learning to occur simultaneously across multiple positive examples.
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公开(公告)号：US20240404154A1
公开(公告)日：2024-12-05
申请号：US18804462
申请日：2024-08-14
Applicant: Google LLC
Inventor： Mikaël Bonnevie , Yuanzhen Li , Ce Liu
Abstract: A multimedia communication system and computer-implemented method for transmitting auxiliary display content to an end-user communication device to be rendered on a display device with a special effect to emphasize an image included in the auxiliary display content, comprising analyzing image data included in an auxiliary display content to detect an object image or a background image, determining a special effect based on the analysis of the image data, applying the special effect to the auxiliary display content to modify display properties for the auxiliary display content such that the object image is emphasized or pops out, and sending the auxiliary display content with modified display properties to the end-user communication device. The special effect can comprise a non-customization special effect, a simple foreground special effect or a selective foreground special effect.
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