Adobe, Inc.

Suryateja Bv

Balaji Vasan Srinivasan

Niyati Himanshu Chhaya

Vishwa Vinay

Stefano Petrangeli

Kuldeep Kulkarni

Aparna Garimella

Sharmila Reddy Nangi

Navita Goyal

Rushil Gupta

Prateksha Udhayanan

Darshan Khandelwal

Chauhan Dev Girishchandra

Parth Satish Laturia

Rajat Jaiswal

Nikhil Kapoor

Elaine Chao

Embodiments are disclosed for user-guided variable-rate compression. A method of user-guided variable-rate compression includes receiving a request to compress an image, the request including the image, a corresponding importance data, and a target bitrate, providing the image, the corresponding importance data, and the target bitrate to a compression network, generating, by the compression network, a learned importance map and a representation of the image, and generating, by the compressing network, a compressed representation of the image based on the learned importance map and the representation of the image.

User-guided variable-rate image compression

Systems and methods for video processing are configured. Embodiments of the present disclosure receive a procedural document comprising a plurality of instructions; extract a plurality of key concepts for an instruction of the plurality of instructions; compute an information coverage distribution for each of a plurality of candidate multi-media assets, wherein the information coverage distribution indicates whether a corresponding multi-media asset relates to each of the plurality of key concepts; select a set of multi-media assets for the instruction based on the information coverage distribution; and generate a multi-media presentation describing the procedural document by combining the set of multi-media assets based on a presentation template.

Auto-generating video to illustrate a procedural document

Embodiments are disclosed for generating an intelligent change summary are described. In some embodiments, a method of generating an intelligent change summary includes obtaining a representation of a plurality of versions of a document, determining a distance score based on a comparison of a first of version of the document and a second version of the document, the distance score representing a magnitude of changes made from the first version of the document to the second version of the document, and generating a change summary of the document based on the distance score.

Intelligent change summarization for designers

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Hyderabad Telangana, India

Suryateja Bv