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I observed that several ground truth segmentation masks provided in the COCO-SEG for certain categories are noisy i.e. the masks are several other objects are also present along with the mask of the desired object. Some examples are cup, tennis racket (humans are segmented along with the racket in the ground truth mask). How should we deal with this? Do you pre-preprocess this dataset somehow? Thanks.
The text was updated successfully, but these errors were encountered:
Thanks for paying attention to this issue. Actually, we did not take these noisy labels into consideration. And this is the main difference between co-segmentation (segment out all the co-objects) and co-saliency detection(segment out only the most salient co-objects), and thus, some other methods will use DUT dataset as we mentioned in the paper for further training to reduce the noise.
If you are interested, you can try to use additional salient datasets to improve the performance.
I observed that several ground truth segmentation masks provided in the COCO-SEG for certain categories are noisy i.e. the masks are several other objects are also present along with the mask of the desired object. Some examples are cup, tennis racket (humans are segmented along with the racket in the ground truth mask). How should we deal with this? Do you pre-preprocess this dataset somehow? Thanks.
The text was updated successfully, but these errors were encountered: