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SODA-D

Introduced in Towards Large-Scale Small Object Detection: Survey and Benchmarks2022

About this Dataset

SODA-D is a large-scale dataset tailored for small object detection in driving scenario, which is built on top of MVD dataset and owned data, where the former is a dataset dedicated to pixel-level understanding of street scenes, and the latter is mainly captured by onboard cameras and mobile phones. With 24704 well-chosen and high-quality images of driving scenarios, SODA-D comprises 277596 instances of 9 categories with horizontal bounding boxes.

Source: Towards Large-Scale Small Object Detection: Survey and Benchmarks

Dataset Variants

SODA-D

Papers1

Towards Large-Scale Small Object Detection: Survey and Benchmarks

The proposed datasets are the first-ever attempt to large-scale benchmarks with a vast collection of exhaustively annotated instances tailored for multi-category SOD, and are expected to facilitate the development of SOD and spawn more breakthroughs in this field.

Tasks

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2D Object Detection Autonomous Driving Small Object Detection

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