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TACO is an open image dataset for litter detection and segmentation, which isgrowing through crowdsourcing. Firstly, this paper describes this dataset andthe tools developed to support it. Secondly, we report instance segmentationperformance using Mask R-CNN on the current version of TACO. Despite its smallsize (1500 images and 4784 annotations), our results are promising on thischallenging problem. However, to achieve satisfactory trash detection in thewild for deployment, TACO still needs much more manual annotations. These canbe contributed using: http://tacodataset.org/

TACO: Trash Annotations in Context for Litter Detection