MBW - Zoo Dataset

Introduced by Dabhi et al. in MBW: Multi-view Bootstrapping in the Wild

Dataset page: https://github.com/mosamdabhi/MBW-Data

MBW - Zoo is a challenging dataset consisting image frames of tail-end distribution categories (such as Fish, Colobus Monkeys, Chimpanzees, etc.) with their corresponding 2D, 3D, and Bounding-Box labels generated from minimal human intervention. Some of the prominent use cases of this dataset include not only sparse 2D and 3D landmark prediction.

The data was collected by two smartphone cameras without any constraints: meaning no guidance or instructions were given as to how the data should be collected. The intention was to mimic the data captured casually by anyone holding a smartphone grade camera. Due to this reason, the cameras were continuously moving in space changing their extrinsics with respect to each other, capturing an in-the-wild dynamic scene. This dataset could be used to benchmark robust algorithms in various computer vision tasks.

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