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公开(公告)号：US20220108131A1
公开(公告)日：2022-04-07
申请号：US17062157
申请日：2020-10-02
Applicant: Adobe Inc.
Inventor： Jason Wen Yong Kuen , Zhe Lin , Jiuxiang Gu
Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately and efficiently learning parameters of a distilled neural network from parameters of a source neural network utilizing multiple augmentation strategies. For example, the disclosed systems can generate lightly augmented digital images and heavily augmented digital images. The disclosed systems can further learn parameters for a source neural network from the lightly augmented digital images. Moreover, the disclosed systems can learn parameters for a distilled neural network from the parameters learned for the source neural network. For example, the disclosed systems can compare classifications of heavily augmented digital images generated by the source neural network and the distilled neural network to transfer learned parameters from the source neural network to the distilled neural network via a knowledge distillation loss function.
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公开(公告)号：US20220078358A1
公开(公告)日：2022-03-10
申请号：US17526853
申请日：2021-11-15
Applicant: Adobe Inc.
Inventor： Lu Zhang , Jianming Zhang , Zhe Lin , Radomir Mech
IPC: H04N5/262 , G11B27/031 , G06K9/00 , G06K9/46
Abstract: Systems and methods provide reframing operations in a smart editing system that may generate a focal point within a mask of an object for each frame of a video segment and perform editing effects on the frames of the video segment to quickly provide users with natural video editing effects. A reframing engine may processes video clips using a segmentation and hotspot module to determine a salient region of an object, generate a mask of the object, and track the trajectory of an object in the video clips. The reframing engine may then receive reframing parameters from a crop suggestion module and a user interface. Based on the determined trajectory of an object in a video clip and reframing parameters, the reframing engine may use reframing logic to produce temporally consistent reframing effects relative to an object for the video clip.
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公开(公告)号：US20220058777A1
公开(公告)日：2022-02-24
申请号：US16997364
申请日：2020-08-19
Applicant: Adobe Inc.
Inventor： Scott David Cohen , Zhihong Ding , Zhe Lin , Mingyang Ling , Luis Angel Figueroa
Abstract: Systems, methods, and software are described herein for removing people distractors from images. A distractor mitigation solution implemented in one or more computing devices detects people in an image and identifies salient regions in the image. The solution then determines a saliency cue for each person and classifies each person as wanted or as an unwanted distractor based at least on the saliency cue. An unwanted person is then removed from the image or otherwise reduced from the perspective of being an unwanted distraction.
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公开(公告)号：US11250548B2
公开(公告)日：2022-02-15
申请号：US16791939
申请日：2020-02-14
Applicant: Adobe Inc.
Inventor： Zhe Lin , Xin Lu , Xiaohui Shen , Jimei Yang , Jiahui Yu
Abstract: Digital image completion using deep learning is described. Initially, a digital image having at least one hole is received. This holey digital image is provided as input to an image completer formed with a framework that combines generative and discriminative neural networks based on learning architecture of the generative adversarial networks. From the holey digital image, the generative neural network generates a filled digital image having hole-filling content in place of holes. The discriminative neural networks detect whether the filled digital image and the hole-filling digital content correspond to or include computer-generated content or are photo-realistic. The generating and detecting are iteratively continued until the discriminative neural networks fail to detect computer-generated content for the filled digital image and hole-filling content or until detection surpasses a threshold difficulty. Responsive to this, the image completer outputs the filled digital image with hole-filling content in place of the holey digital image's holes.
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185.发明授权公开(公告)号：US11244195B2
公开(公告)日：2022-02-08
申请号：US15967928
申请日：2018-05-01
Applicant: Adobe Inc.
Inventor： I-Ming Pao , Zhe Lin , Sarah Stuckey , Jianming Zhang , Betty Leong
Abstract: The present disclosure relates to systems, method, and computer readable media that iteratively apply a neural network to a digital image at a reduced resolution to automatically identify pixels of salient objects portrayed within the digital image. For example, the disclosed systems can generate a reduced-resolution digital image from an input digital image and apply a neural network to identify a region corresponding to a salient object. The disclosed systems can then iteratively apply the neural network to additional reduced-resolution digital images (based on the identified region) to generate one or more reduced-resolution segmentation maps that roughly indicate pixels of the salient object. In addition, the systems described herein can perform post-processing based on the reduced-resolution segmentation map(s) and the input digital image to accurately determine pixels that correspond to the salient object.
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Patent Agency Ranking
公开(公告)号：US20220036127A1
公开(公告)日：2022-02-03
申请号：US16943511
申请日：2020-07-30
Applicant: Adobe Inc.
Inventor： Zhe Lin , Xihui Liu , Quan Hung Tran , Jianming Zhang , Handong Zhao
Abstract: The technology described herein is directed to a reinforcement learning based framework for training a natural media agent to learn a rendering policy without human supervision or labeled datasets. The reinforcement learning based framework feeds the natural media agent a training dataset to implicitly learn the rendering policy by exploring a canvas and minimizing a loss function. Once trained, the natural media agent can be applied to any reference image to generate a series (or sequence) of continuous-valued primitive graphic actions, e.g., sequence of painting strokes, that when rendered by a synthetic rendering environment on a canvas, reproduce an identical or transformed version of the reference image subject to limitations of an action space and the learned rendering policy.
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公开(公告)号：US11238362B2
公开(公告)日：2022-02-01
申请号：US14996959
申请日：2016-01-15
Applicant: Adobe Inc.
Inventor： Hailin Jin , Zhou Ren , Zhe Lin , Chen Fang
Abstract: Modeling semantic concepts in an embedding space as distributions is described. In the embedding space, both images and text labels are represented. The text labels describe semantic concepts that are exhibited in image content. In the embedding space, the semantic concepts described by the text labels are modeled as distributions. By using distributions, each semantic concept is modeled as a continuous cluster which can overlap other clusters that model other semantic concepts. For example, a distribution for the semantic concept “apple” can overlap distributions for the semantic concepts “fruit” and “tree” since can refer to both a fruit and a tree. In contrast to using distributions, conventionally configured visual-semantic embedding spaces represent a semantic concept as a single point. Thus, unlike these conventionally configured embedding spaces, the embedding spaces described herein are generated to model semantic concepts as distributions, such as Gaussian distributions, Gaussian mixtures, and so on.
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公开(公告)号：US20220012885A1
公开(公告)日：2022-01-13
申请号：US17483280
申请日：2021-09-23
Applicant: Adobe Inc.
Inventor： Zhe Lin , Jianming Zhang , He Zhang , Federico Perazzi
Abstract: The present disclosure relates to utilizing a neural network having a two-stream encoder architecture to accurately generate composite digital images that realistically portray a foreground object from one digital image against a scene from another digital image. For example, the disclosed systems can utilize a foreground encoder of the neural network to identify features from a foreground image and further utilize a background encoder to identify features from a background image. The disclosed systems can then utilize a decoder to fuse the features together and generate a composite digital image. The disclosed systems can train the neural network utilizing an easy-to-hard data augmentation scheme implemented via self-teaching. The disclosed systems can further incorporate the neural network within an end-to-end framework for automation of the image composition process.
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公开(公告)号：US11216505B2
公开(公告)日：2022-01-04
申请号：US16561973
申请日：2019-09-05
Applicant: Adobe Inc.
Inventor： Saeid Motiian , Zhe Lin , Samarth Gulati , Pramod Srinivasan , Jose Ignacio Echevarria Vallespi , Baldo Antonio Faieta
IPC: G06F16/00 , G06F16/583 , G06F17/16 , G06F16/55 , G06F16/532
Abstract: In implementations of multi-resolution color-based image search, an image search system determines a color vector for a query image based on a color histogram of the query image by concatenating two color histograms having different resolutions. The image search system can compute distance measures between the color vector of the query image and color vectors of candidate images. The image search system can select one or more of the candidate images to return based on the distance measures utilizing the distance measures as indication of color similarity of the candidate images to the query image.
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公开(公告)号：US11184558B1
公开(公告)日：2021-11-23
申请号：US16900435
申请日：2020-06-12
Applicant: ADOBE INC.
Inventor： Lu Zhang , Jianming Zhang , Zhe Lin , Radomir Mech
IPC: H04N5/262 , G11B27/031 , G06K9/00 , G06K9/46
Abstract: Systems and methods provide reframing operations in a smart editing system that may generate a focal point within a mask of an object for each frame of a video segment and perform editing effects on the frames of the video segment to quickly provide users with natural video editing effects. A reframing engine may processes video clips using a segmentation and hotspot module to determine a salient region of an object, generate a mask of the object, and track the trajectory of an object in the video clips. The reframing engine may then receive reframing parameters from a crop suggestion module and a user interface. Based on the determined trajectory of an object in a video clip and reframing parameters, the reframing engine may use reframing logic to produce temporally consistent reframing effects relative to an object for the video clip.
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