ArXiv Models Models trained on UVH 26 deliver up to 31.5% higher mAP than COCO pretrained baselines, demonstrating significant gains in real world performance for Indian traffic scenarios. Dataset Card for UVH 26 (Urban Vision Hackathon Dataset) Dataset Summary UVH 26 is a large scale, India specific traffic camera image dataset released by AIM @ IISc for research in intelligent transportation systems and vehicle detection. It contains 26,646 high resolution (1080p) frames sampled from ≈ 2,800 Bengaluru Safe City CCTV cameras over a 4 week period. Images were annotated through a nationwide crowdsourced hackathon involving 565 college students , producing ≈ 1.8 million bounding boxes across 14 fine grained vehicle classes representative of Indian traffic conditions. To capture different levels of annotation consensus, UVH 26 includes two separate annotation sets : 1. UVH 26 MV — final labels computed via majority voting across multiple annotators per image. 2. UVH 26 ST — labels generated using the STAPLE algorithm (an Expectation–Maximization–based probabilistic consensus method) for higher reliability. These versions share identical image data but differ in bounding box consensus…
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