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Fail to get the same results #6

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neineimeow opened this issue Dec 26, 2020 · 3 comments
Open

Fail to get the same results #6

neineimeow opened this issue Dec 26, 2020 · 3 comments

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@neineimeow
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Hi ! Thanks for your wonderful work ~But i fail to get as well as results in your paper. Can you post the ga results with VGG16 backbone in cityscape->foggy cityscape ?
GA:
Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.174
Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.331
Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.157
Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.019
Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.156
Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.359
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.146
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.263
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.286
Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.052
Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.262
Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.560

GA_CA:
Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.183
Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.340
Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.164
Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.023
Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.163
Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.370
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.149
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.280
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.302
Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.050
Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.279
Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.582

@mochaojie
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Hi, i have received the cityscapes dataset. However, when i click the link for foggy cityscapes, i don't know which one is i really need. In the website, i see some foggy cityscapes datasets for semantic segmentation, not for object detection. Can you give me the link for foggy dataset specifically. Thanks!

@neineimeow
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Foggy cityscapes need u email to their team. You can see it on cityscape homepage

@Changes92
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Hi ! Thanks for your wonderful work ~But i fail to get as well as results in your paper. Can you post the ga results with VGG16 backbone in cityscape->foggy cityscape ?
GA:
Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.174
Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.331
Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.157
Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.019
Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.156
Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.359
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.146
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.263
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.286
Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.052
Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.262
Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.560

GA_CA:
Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.183
Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.340
Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.164
Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.023
Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.163
Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.370
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.149
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.280
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.302
Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.050
Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.279
Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.582

Hi, are these the best AP50 results selected in your experiments? I find that the results are sensitive to the training iteration. If I choose some inappropriate iteration to evaluate, the result will be very bad. How about yours? Thanks

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