Comments (3)
Hi @qiudi0127 , thanks for the question. I think it is similar to #50.
Basically, it is very likely that better feature extractor would lead to better clustering results. However, as all clustering algorithms can benefit from stronger feature extractor, it is uncertain that the performance gap between our method and baseline methods will enlarge continuously. More experiments are required to show the change of performance gap.
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@yl-1993 hi, i met an issue that using the part1_test.bin and pretrained model can not get the fscore given by git.
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Hi @qiudi0127 , it seems that the k
is set to 15 instead of 80 for testing?
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Related Issues (20)
- output error HOT 1
- Dataset issue HOT 2
- Issue while training LGCN HOT 1
- 您好,想请教一下训练GCN-D时报错run out of input HOT 1
- 没有修改任何参数跑作者提供的pretrained model for ms1m Fscore 只有0.32
- Clustering 512D features using pretrained model HOT 3
- building symmetric adjacency matrix in utils HOT 1
- why using output of relu for rebuilding knn graph HOT 1
- is not a checkpoint filemodels/pretrained_gcn_e_ms1m.pth HOT 3
- about extracting features HOT 3
- About how to make a .meta file HOT 1
- Can we manually set the number of clusters during the test HOT 1
- 大佬,请教下train_cluster_seg_iop_vox.sh 的test阶段报错的问题 HOT 2
- 两个face recognition模型,推荐使用哪个,hfsoftmax还要用到python 2 ? HOT 1
- About pretrained_model to get the the extracted feature HOT 2
- GCN-D MMdistributedDataparallel train HOT 2
- 关于性能 HOT 1
- How to apply lgcn for clustering on custom embeddings of collected face images? HOT 1
- On custom dataset preparation
- On the numpy version which may cause exception HOT 3
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