Google llc (20240114158). Hierarchical Video Encoders simplified abstract

Hierarchical Video Encoders

Organization Name

google llc

Inventor(s)

Vihan Jain of San Francisco CA (US)

Joonseok Lee of Fremont CA (US)

Ming Zhao of Sunnyvale CA (US)

Sheide Chammas of San Francisco CA (US)

Hexiang Hu of Los Angeles CA (US)

Bowen Zhang of Los Angeles CA (US)

Fei Sha of Los Angeles CA (US)

Tze Way Eugene Ie of Los Altos CA (US)

Hierarchical Video Encoders - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240114158 titled 'Hierarchical Video Encoders

Simplified Explanation

The computer-implemented method described in the abstract involves generating video representations using a hierarchical video encoder. Here is a simplified explanation of the patent application:

• Frames of a video are processed using a machine-learned frame-level encoder model to generate frame representations.
• These frame representations are used to determine segment representations for different video segments.
• The segment representations are then processed with a machine-learned segment-level encoder model to generate contextualized segment representations.
• A video representation is determined based on these contextualized segment representations and provided as an output.

1. 1. 1. Potential Applications

- Video editing software - Video compression technology

1. 1. 1. Problems Solved

- Efficient video representation generation - Improved video encoding process

1. 1. 1. Benefits

- Higher quality video representations - Faster video processing

1. 1. 1. Potential Commercial Applications
         1. Optimizing Video Encoding with Hierarchical Video Encoder

1. 1. 1. Possible Prior Art

There are existing video encoding techniques that utilize machine learning models to improve video compression and quality. However, the specific hierarchical approach described in this patent application may be a novel innovation in the field.

1. 1. 1. 1. Unanswered Questions
         2. How does the hierarchical video encoder compare to traditional video encoding methods?

The article does not provide a direct comparison between the hierarchical video encoder and traditional video encoding methods. It would be helpful to understand the specific advantages and disadvantages of this new approach.

1. 1. 1. 1. What kind of machine learning models are used in the frame-level and segment-level encoders?

The abstract mentions machine-learned models for processing frames and segments, but it does not specify the exact type of machine learning models used. More information on the specific algorithms or techniques employed would be beneficial for a deeper understanding of the technology.

Original Abstract Submitted

a computer-implemented method for generating video representations utilizing a hierarchical video encoder includes obtaining a video, wherein the video includes a plurality of frames, processing each of the plurality of frames with a machine-learned frame-level encoder model to respectively generate a plurality of frame representations for the plurality of frames, the plurality of frame representations respective to the plurality of frames determining a plurality of segment representations representative of a plurality of video segments including one or more of the plurality of frames, the plurality of segment representations based at least in part on the plurality of frame representations, processing the plurality of segment representations with a machine-learned segment-level encoder model to generate a plurality of contextualized segment representations, determining a video representation based at least in part on the plurality of contextualized segment representations, and providing the video representation as an output.