Hi,
I use this open-source code to evaluate da_faster on voc-clipart.
The dataset I used as follows:
source dataset: VOC07+12 trainval, 16k images all.
target dataset: clipart1k (train+test)
And I got higher score(voc07 metric, IoU=0.5) than your papers:
mAP: 0.3296aeroplane : 0.2564bicycle : 0.4188bird : 0.2848boat : 0.2978bottle : 0.3248bus : 0.3452car : 0.3970cat : 0.0805chair : 0.3393cow : 0.4999diningtable : 0.1703dog : 0.2019horse : 0.3035motorbike : 0.3662person : 0.5565pottedplant : 0.4436sheep : 0.1996sofa : 0.2630train : 0.3749tvmonitor : 0.4676
Following is the soruce-only score of clipart1k:
mAP: 0.2754aeroplane : 0.1798bicycle : 0.4767bird : 0.2161boat : 0.1275bottle : 0.2338bus : 0.6437car : 0.3147cat : 0.1322chair : 0.3185cow : 0.1364diningtable : 0.1931dog : 0.1273horse : 0.2536motorbike : 0.4130person : 0.3196pottedplant : 0.3662sheep : 0.0909sofa : 0.2208train : 0.4274tvmonitor : 0.3165
I just do not know there was anything wrong with my experiment or anything else, because my result(Map50=0.3296) was much higher than your papers (mAP50=19.8)
Hi,
I use this open-source code to evaluate da_faster on voc-clipart.
The dataset I used as follows:
source dataset: VOC07+12 trainval, 16k images all.
target dataset: clipart1k (train+test)
And I got higher score(voc07 metric, IoU=0.5) than your papers:
Following is the soruce-only score of clipart1k:
I just do not know there was anything wrong with my experiment or anything else, because my result(Map50=0.3296) was much higher than your papers (mAP50=19.8)