Invention Grant
- Patent Title: Temporal-based deformable kernels
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Application No.: US16219713Application Date: 2018-12-13
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Publication No.: US12118445B1Publication Date: 2024-10-15
- Inventor: Sarah Tariq
- Applicant: Zoox, Inc.
- Applicant Address: US CA Foster City
- Assignee: Zoox, Inc.
- Current Assignee: Zoox, Inc.
- Current Assignee Address: US CA Foster City
- Agency: Lee & Hayes, P.C.
- Main IPC: G06K9/62
- IPC: G06K9/62 ; B60K31/00 ; G06N3/084 ; G06N20/10 ; G06T7/20 ; G06T7/254 ; G06T7/70 ; G06V10/24 ; G06V10/36 ; G06V10/44 ; G06V10/70 ; G06V10/75

Abstract:
Techniques are disclosed for implementing a convolutional neural network that determines an offset field for deforming a kernel to be used in a convolution. The offset field is temporally-based, at least in part, on data generated at an earlier time. Furthermore, techniques are disclosed for using sensor data to train a neural network to learn shapes or configurations of such deformed kernels. The temporal-based deformable convolutions may be used for object identification, object matching, object classification, segmentation, and/or object tracking, in various examples.
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