Invention Application
- Patent Title: TEMPORALLY DISTRIBUTED NEURAL NETWORKS FOR VIDEO SEMANTIC SEGMENTATION
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Application No.: US17735156Application Date: 2022-05-03
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Publication No.: US20220270370A1Publication Date: 2022-08-25
- Inventor: Federico Perazzi , Zhe Lin , Ping Hu , Oliver Wang , Fabian David Caba Heilbron
- Applicant: Adobe Inc.
- Applicant Address: US CA San Jose
- Assignee: Adobe Inc.
- Current Assignee: Adobe Inc.
- Current Assignee Address: US CA San Jose
- Main IPC: G06V20/40
- IPC: G06V20/40 ; G06N3/04 ; G06T7/11 ; G06F17/15

Abstract:
A Video Semantic Segmentation System (VSSS) is disclosed that performs accurate and fast semantic segmentation of videos using a set of temporally distributed neural networks. The VSSS receives as input a video signal comprising a contiguous sequence of temporally-related video frames. The VSSS extracts features from the video frames in the contiguous sequence and based upon the extracted features, selects, from a set of labels, a label to be associated with each pixel of each video frame in the video signal. In certain embodiments, a set of multiple neural networks are used to extract the features to be used for video segmentation and the extraction of features is distributed among the multiple neural networks in the set. A strong feature representation representing the entirety of the features is produced for each video frame in the sequence of video frames by aggregating the output features extracted by the multiple neural networks.
Public/Granted literature
- US11854206B2 Temporally distributed neural networks for video semantic segmentation Public/Granted day:2023-12-26
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