Unlocking AI Perception Gains with Iterative Synthetic Data Generation

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  • เผยแพร่เมื่อ 22 ธ.ค. 2024

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  • @paralleldomain3649
    @paralleldomain3649  ปีที่แล้ว

    Timestamps:
    00:00: Introducing Omar and Phillip
    01:12: How to Get Value Out of Synthetic Data
    02:06: Agenda
    02:54: Problems with Current ML Development Practices
    04:23: Edge Case Detection using Synthetic Data
    05:11: Parallel Domain’s Image Data (parking, trailers, debris, road signs, etc.)
    05:45: Parallel Domain’s Sensors and Annotation types (labels)
    06:19: Performance Improvements using Synthetic Data
    07:45: Iterative Synthetic Dataset Design
    09:15: Domain Gap Ontology
    25:29 Parallel Domain SDK
    28:46 Demo - using Synthetic Data for 2D Object Detection
    32:11 Demo - Performance Iteration with Synthetic Data
    35:11 Dataset Design - Optical Flow Example
    39:54 Dataset Design - Semantic Segmentation UDA Example
    43:43 Demo - Reducing Synthetic Data Iteration Times using Statistics
    47:41 Why Parallel Domain
    48:44 Parallel Domain at CVPR
    51:24 Questions and Answers