The FCN-8 example uses the VOC2007 and VOC2012 datasets for training and the VOC2007 dataset for evaluation. However the VOC2012 train dataset contains the VOC2007 train and test images.
So basically you use a part of the train dataset to evaluate the network! No surprise that the results are nearly perfect!
With other images the results are really mediocre. Here's an example (the cyclist is segmented as bicycle(green) or dog (dark blue), the bike as person (pink) or car (cyan), the regions are quite random...)
Still have to check the performance of FCN-8 with other implementations to see if it's an implementation problem, or this is the normal performance of the FCN-8 network.
YunYang1994
commented
5 years ago
The FCN-8 example uses the VOC2007 and VOC2012 datasets for training and the VOC2007 dataset for evaluation. However the VOC2012 train dataset contains the VOC2007 train and test images.
So basically you use a part of the train dataset to evaluate the network! No surprise that the results are nearly perfect!
With other images the results are really mediocre. Here's an example (the cyclist is segmented as bicycle(green) or dog (dark blue), the bike as person (pink) or car (cyan), the regions are quite random...)
Still have to check the performance of FCN-8 with other implementations to see if it's an implementation problem, or this is the normal performance of the FCN-8 network.