I have trouble in setting up the experimental environment on the public server, so I use a stronger baseline that can reach mIoU 59.8 after fine-tuning on novel classes with five samples in each class.
However, the replacement with class label embeddings (w2c+ Fasttext) cannot reproduce the result reported in the Figure5(b) (about 75 mIoU) but yields close results (60.1 mIoU) to baseline even after fine-tuning on novel class and calibration parameter tuning (threshold=0.5 works best in my case).
Has anyone successfully reproduced the GFLSS results on PASCAL VOC using DeeplabV2 or other base frameworks?
I have trouble in setting up the experimental environment on the public server, so I use a stronger baseline that can reach mIoU 59.8 after fine-tuning on novel classes with five samples in each class.
However, the replacement with class label embeddings (w2c+ Fasttext) cannot reproduce the result reported in the Figure5(b) (about 75 mIoU) but yields close results (60.1 mIoU) to baseline even after fine-tuning on novel class and calibration parameter tuning (threshold=0.5 works best in my case).
Has anyone successfully reproduced the GFLSS results on PASCAL VOC using DeeplabV2 or other base frameworks?