Patents by Inventor Salil TAMBE
Salil TAMBE 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).
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Publication number: 20230281763Abstract: Methods, systems, and non-transitory computer readable storage media are disclosed for utilizing a plurality of neural networks in a multi-branch pipeline to generate image masks for digital images. Specifically, the disclosed system can classify a digital image as a portrait or a non-portrait image. Based on classifying a portrait image, the disclosed system can utilize separate neural networks to generate a first mask portion for a portion of the digital image including a defined boundary region and a second mask portion for a portion of the digital image including a blended boundary region. The disclosed system can generate the mask portion for the blended boundary region by utilizing a trimap generation neural network to automatically generate a trimap segmentation including the blended boundary region. The disclosed system can then merge the first mask portion and the second mask portion to generate an image mask for the digital image.Type: ApplicationFiled: May 15, 2023Publication date: September 7, 2023Inventors: He Zhang, Seyed Morteza Safdarnejad, Yilin Wang, Zijun Wei, Jianming Zhang, Salil Tambe, Brian Price
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Patent number: 11651477Abstract: Methods, systems, and non-transitory computer readable storage media are disclosed for utilizing a plurality of neural networks in a multi-branch pipeline to generate image masks for digital images. Specifically, the disclosed system can classify a digital image as a portrait or a non-portrait image. Based on classifying a portrait image, the disclosed system can utilize separate neural networks to generate a first mask portion for a portion of the digital image including a defined boundary region and a second mask portion for a portion of the digital image including a blended boundary region. The disclosed system can generate the mask portion for the blended boundary region by utilizing a trimap generation neural network to automatically generate a trimap segmentation including the blended boundary region. The disclosed system can then merge the first mask portion and the second mask portion to generate an image mask for the digital image.Type: GrantFiled: August 7, 2020Date of Patent: May 16, 2023Assignee: Adobe Inc.Inventors: He Zhang, Seyed Morteza Safdarnejad, Yilin Wang, Zijun Wei, Jianming Zhang, Salil Tambe, Brian Price
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Publication number: 20230129341Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that generate preliminary object masks for objects in an image, surface the preliminary object masks as object mask previews, and on-demand converts preliminary object masks into refined object masks. Indeed, in one or more implementations, an object mask preview and on-demand generation system automatically detects objects in an image. For the detected objects, the object mask preview and on-demand generation system generates preliminary object masks for the detected objects of a first lower resolution. The object mask preview and on-demand generation system surfaces a given preliminary object mask in response to detecting a first input. The object mask preview and on-demand generation system also generates a refined object mask of a second higher resolution in response to detecting a second input.Type: ApplicationFiled: January 25, 2022Publication date: April 27, 2023Inventors: Betty Leong, Hyunghwan Byun, Alan L Erickson, Chih-Yao Hsieh, Sarah Kong, Seyed Morteza Safdarnejad, Salil Tambe, Yilin Wang, Zijun Wei, Zhengyun Zhang
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Patent number: 11393100Abstract: Methods, systems, and non-transitory computer readable storage media are disclosed for utilizing a plurality of neural networks in a multi-branch pipeline to generate image masks for digital images. Specifically, the disclosed system can classify a digital image as a portrait or a non-portrait image. Based on classifying a portrait image, the disclosed system can utilize separate neural networks to generate a first mask portion for a portion of the digital image including a defined boundary region and a second mask portion for a portion of the digital image including a blended boundary region. The disclosed system can generate the mask portion for the blended boundary region by utilizing a trimap generation neural network to automatically generate a trimap segmentation including the blended boundary region. The disclosed system can then merge the first mask portion and the second mask portion to generate an image mask for the digital image.Type: GrantFiled: August 7, 2020Date of Patent: July 19, 2022Assignee: Adobe Inc.Inventors: He Zhang, Seyed Morteza Safdarnejad, Yilin Wang, Zijun Wei, Jianming Zhang, Salil Tambe, Brian Price
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Publication number: 20220044366Abstract: Methods, systems, and non-transitory computer readable storage media are disclosed for utilizing a plurality of neural networks in a multi-branch pipeline to generate image masks for digital images. Specifically, the disclosed system can classify a digital image as a portrait or a non-portrait image. Based on classifying a portrait image, the disclosed system can utilize separate neural networks to generate a first mask portion for a portion of the digital image including a defined boundary region and a second mask portion for a portion of the digital image including a blended boundary region. The disclosed system can generate the mask portion for the blended boundary region by utilizing a trimap generation neural network to automatically generate a trimap segmentation including the blended boundary region. The disclosed system can then merge the first mask portion and the second mask portion to generate an image mask for the digital image.Type: ApplicationFiled: August 7, 2020Publication date: February 10, 2022Inventors: He Zhang, Seyed Morteza Safdarnejad, Yilin Wang, Zijun Wei, Jianming Zhang, Salil Tambe, Brian Price
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Publication number: 20220044365Abstract: Methods, systems, and non-transitory computer readable storage media are disclosed for utilizing a plurality of neural networks in a multi-branch pipeline to generate image masks for digital images. Specifically, the disclosed system can classify a digital image as a portrait or a non-portrait image. Based on classifying a portrait image, the disclosed system can utilize separate neural networks to generate a first mask portion for a portion of the digital image including a defined boundary region and a second mask portion for a portion of the digital image including a blended boundary region. The disclosed system can generate the mask portion for the blended boundary region by utilizing a trimap generation neural network to automatically generate a trimap segmentation including the blended boundary region. The disclosed system can then merge the first mask portion and the second mask portion to generate an image mask for the digital image.Type: ApplicationFiled: August 7, 2020Publication date: February 10, 2022Inventors: He Zhang, Seyed Morteza Safdarnejad, Yilin Wang, Zijun Wei, Jianming Zhang, Salil Tambe, Brian Price
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Patent number: 9843787Abstract: Certain aspects relate to systems and techniques for efficiently recording captured plenoptic image data and for rendering images from the captured plenoptic data. The plenoptic image data can be captured by a plenoptic or other light field camera. In some implementations, four dimensional radiance data can be transformed into three dimensional data by performing a Radon transform to define the image by planes instead of rays. A resulting Radon image can represent the summed values of energy over each plane. The original three-dimensional luminous density of the scene can be recovered, for example, by performing an inverse Radon transform. Images from different views and/or having different focus can be rendered from the luminous density.Type: GrantFiled: April 24, 2014Date of Patent: December 12, 2017Assignee: QUALCOMM IncorporatedInventors: Todor Georgiev Georgiev, Salil Tambe
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Patent number: 9633250Abstract: A method for face alignment operates on a face image and a set of intitial landmark locations by first aligning globally the initial locations to a set of landmark locations of a face with a prototype shape to obtain global alignment parameters, and then warping the initial locations and the image from a coordinate frame of the image to a coordinate frame of the prototype shape according to the global alignment parameters to obtain warped landmark locations and a warped face image. Features are extracted from the warped face image at the warped landmark locations, and a regression function is applied to the features to obtain updated landmark locations in the coordinate frame of the prototype shape. Finally, the updated landmark locations in the coordinate frame of the prototype shape are warped to the coordinate frame of the image, to obtain updated landmark locations.Type: GrantFiled: September 21, 2015Date of Patent: April 25, 2017Assignee: Mitsubishi Electric Research Laboratories, Inc.Inventors: Oncel Tuzel, Tim Marks, Salil Tambe
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Publication number: 20170083751Abstract: A method for face alignment operates on a face image and a set of initial landmark locations by first aligning globally the initial locations to a set of landmark locations of a face with a prototype shape to obtain global alignment parameters, and then warping the initial locations and the image from a coordinate frame of the image to a coordinate frame of the prototype shape according to the global alignment parameters to obtain warped landmark locations and a warped face image. Features are extracted from the warped face image at the warped landmark locations, and a regression function is applied to the features to obtain updated landmark locations in the coordinate frame of the prototype shape. Finally, the updated landmark locations in the coordinate frame of the prototype shape are warped to the coordinate frame of the image, to obtain updated landmark locations.Type: ApplicationFiled: September 21, 2015Publication date: March 23, 2017Inventors: Oncel Tuzel, Tim Marks, Salil Tambe
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Patent number: 9420201Abstract: Provided is an image processing apparatus including an image generation unit that, from photographic images that are captured using multiple photographic parameters, generates an image of which values of the multiple photographic parameters are different from values of the photographic image.Type: GrantFiled: January 12, 2015Date of Patent: August 16, 2016Assignees: SONY CORPORATION, WILLIAM MARSH RICE UNIVERSITYInventors: Atsushi Ito, Ashok Veeraraghavan, Kaushik Mitra, Salil Tambe
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Publication number: 20150312549Abstract: Certain aspects relate to systems and techniques for efficiently recording captured plenoptic image data and for rendering images from the captured plenoptic data. The plenoptic image data can be captured by a plenoptic or other light field camera. In some implementations, four dimensional radiance data can be transformed into three dimensional data by performing a Radon transform to define the image by planes instead of rays. A resulting Radon image can represent the summed values of energy over each plane. The original three-dimensional luminous density of the scene can be recovered, for example, by performing an inverse Radon transform. Images from different views and/or having different focus can be rendered from the luminous density.Type: ApplicationFiled: April 24, 2014Publication date: October 29, 2015Applicant: QUALCOMM IncorporatedInventors: Todor Georgiev Georgiev, Salil Tambe
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Publication number: 20150206314Abstract: Provided is an image processing apparatus including an image generation unit that, from photographic images that are captured using multiple photographic parameters, generates an image of which values of the multiple photographic parameters are different from values of the photographic image.Type: ApplicationFiled: January 12, 2015Publication date: July 23, 2015Applicants: SONY CORPORATION, WILLIAM MARSH RICE UNIVERSITYInventors: Atsushi ITO, Ashok VEERARAGHAVAN, Kaushik MITRA, Salil TAMBE