arXiv · 2003.06975
TACO: Trash Annotations in Context for Litter Detection
Abstract
TACO is an open image dataset for litter detection and segmentation, which is growing through crowdsourcing. Firstly, this paper describes this dataset and the tools developed to support it. Secondly, we report instance segmentation performance using Mask R-CNN on the current version of TACO. Despite its small size (1500 images and 4784 annotations), our results are promising on this challenging problem. However, to achieve satisfactory trash detection in the wild for deployment, TACO still needs much more manual annotations. These can be contributed using: http://tacodataset.org/
Explore related subjects
Keep this discovery
Pedro F Proença, Pedro Simões. 2020-03-16. TACO: Trash Annotations in Context for Litter Detection. https://arxiv.org/abs/2003.06975
Cite the original work for its findings. Save a collection to share your selection of sources.