Invention Publication
- Patent Title: ALIAS-FREE COMPRESSION OF CONTENT USING ARTIFICIAL NEURAL NETWORKS
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Application No.: US18188070Application Date: 2023-03-22
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Publication No.: US20240323415A1Publication Date: 2024-09-26
- Inventor: David Wilson ROMERO GUZMAN , Gabriele CESA , Guillaume Konrad SAUTIERE , Yunfan ZHANG , Taco Sebastiaan COHEN , Auke Joris WIGGERS
- Applicant: QUALCOMM Incorporated
- Applicant Address: US CA San Diego
- Assignee: QUALCOMM Incorporated
- Current Assignee: QUALCOMM Incorporated
- Current Assignee Address: US CA San Diego
- Main IPC: H04N19/42
- IPC: H04N19/42 ; G06T3/40 ; H04N19/182

Abstract:
Certain aspects of the present disclosure provide techniques and apparatus for encoding content using a neural network. An example method generally includes encoding video content into a latent space representation through an encoder implemented by a first machine learning model. A code is generated by upsampling the latent space representation of the video content. A prior is calculated based on a conditional probability of obtaining the upsampled latent space representation conditioned by the latent space representation of the video content. A compressed version of the video content is generated based on a probabilistic model implemented by a second machine learning model, the generated code, and the calculated prior, and the compressed version of the video content is output for transmission.
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