megvii-research BBN issues

megvii-research / BBN

The official PyTorch implementation of paper BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition

https://arxiv.org/abs/1912.02413

MIT License

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why I have a question that i never seen it, ABOUT shutil.Error

#40 Liugazn closed 5 months ago
1
about train2018.json

#39 lmqomo12 opened 7 months ago
1
Bump pillow from 6.2.0 to 9.3.0

#38 dependabot[bot] opened 1 year ago
0
Bump numpy from 1.16.3 to 1.22.0

#37 dependabot[bot] opened 2 years ago
0
Bump pillow from 6.2.0 to 9.0.1

#36 dependabot[bot] closed 1 year ago
1
.

#35 aishawariya-athawale closed 2 years ago
0
Bump pillow from 6.2.0 to 9.0.0

#34 dependabot[bot] closed 2 years ago
1
Bump opencv-python from 4.1.0.25 to 4.2.0.32

#33 dependabot[bot] opened 2 years ago
0
Bump opencv-python from 4.1.0.25 to 4.1.1.26

#32 dependabot[bot] closed 2 years ago
1
Bump pillow from 6.2.0 to 8.3.2

#31 dependabot[bot] closed 2 years ago
1
feature compactness calculation

#30 IssacCyj opened 2 years ago
0
Could you release the pretrained models for CIFAR?

#29 liming-ai opened 2 years ago
0
Bump pillow from 6.2.0 to 8.2.0

#28 dependabot[bot] closed 2 years ago
1
is it possible that I implement this method using Keras?

#27 Cocoalate opened 3 years ago
1
Different hyperparameters between paper and code

#26 liming-ai opened 3 years ago
1
About the implementation of in the cumulative learning stage

#25 YTEP-ZHI closed 2 months ago
2
Bump pyyaml from 5.1 to 5.4

#24 dependabot[bot] opened 3 years ago
0
Bump pillow from 6.2.0 to 8.1.1

#23 dependabot[bot] closed 3 years ago
1
How can I use this method in yolov5?

#22 JiangWeiHn opened 3 years ago
0
about validation

#21 hanyu-Liang closed 3 years ago
0
Any improvement if BBN is utilized in object detection?

#20 handsomefengfeng opened 3 years ago
1
If I follow the default setting and run python main/train.py --cfg configs/cifar10.yaml, I cannot achieve similar results as reported in your paper.At the beginning, the loss of training set decreases, and the accuracy of verification set increases. However, after running for a period of time, the loss of training set will increase, and the accuracy of verification set will decrease, and fluctuate greatly. What's the matter?

#19 ghost opened 3 years ago
3
how to get long-tail cifar

#18 xiaohua-chen opened 3 years ago
1
Accuracy on ImageNet-LT

#17 pengzhiliang opened 3 years ago
4
what is the mean of the "2× scheduler" in the section 5.4.2?

#16 Wondersui opened 4 years ago
3
Multiplying by 2 when concatenate the mix feature?

#15 anthonytmh closed 4 years ago
0
aggregate feature

#14 abcxs closed 4 years ago
1
Confusions about reverse sampler

#13 Hwang64 opened 4 years ago
2
load model from pretrain model error

#12 Vickeyhw opened 4 years ago
1
Section 3 Implementation details

#11 miaoct opened 4 years ago
1
Questions about mix_feature

#10 mingliangzhang2018 closed 4 years ago
0
Does the setting in this code correspond to Table 1 result on CIFAR ?

#9 jiequancui opened 4 years ago
6
Training Time for iNaturalist'18

#8 duggalrahul closed 4 years ago
2
AttributeError: 'IMBALANCECIFAR10' object has no attribute 'data'

#7 xinfu607 opened 4 years ago
1
您好，请问训练时，采用的loss是CSCE么？

#6 gengyanlei closed 4 years ago
0
Bump pillow from 6.0.0 to 6.2.0

#5 dependabot[bot] closed 4 years ago
0
cifar10 results and imb_type

#4 latstars closed 4 years ago
2
question about loss curve at inaturalist2019

#3 Haijunlv closed 4 years ago
2
Difference between paper and code

#2 valencebond closed 4 years ago
4
Pretrained INaturalist models llink is not working

#1 alishsuper closed 4 years ago
9