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SydneyScapes: Image Segmentation for Australian Environments

arXiv 2504.07542 ↗First posted 10 Apr 2025cs.CVcited by 0

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Abstract (arXiv)

Autonomous Vehicles (AVs) are being partially deployed and tested across various global locations, including China, the USA, Germany, France, Japan, Korea, and the UK, but with limited demonstrations in Australia. The integration of machine learning (ML) into AV perception systems highlights the need for locally labelled datasets to develop and test algorithms in specific environments. To address this, we introduce SydneyScapes - a dataset tailored for computer vision tasks of image semantic, instance, and panoptic segmentation. This dataset, collected from Sydney and surrounding cities in New South Wales (NSW), Australia, consists of 756 images with high-quality pixel-level annotations. It is designed to assist AV industry and researchers by providing annotated data and tools for algorithm development, testing, and deployment in the Australian context. Additionally, we offer benchmarking results using state-of-the-art algorithms to establish reference points for future research and development. The dataset is publicly available at https://hdl.handle.net/2123/33051.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 25 of its 33 references that are in the map. First posted on arXiv 10 Apr 2025.

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References · 25

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13 more
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