hbdat / cvpr20_lesa Goto Github PK

Hello Dat,
The total length of the top unseen is 400 but it's 399 at L55 of the training file.
It would be great if you could let me know the correct number.

Thanks in advance,
Akshita

Thank you for sharing the code.
In the "extract_data" folder, there is no file with the name "extract_full_NUS_WIDE_images_attention_VGG_feature_2_TFRecord.py", which according to the instruction is needed for extracting features into TensorFlow storage format. Could you please clarify whether this is a typo error or the actual file is missing from this repo.

Thank you for providing the code for your wonderful paper. The current version of the code is highly dependent on the datasets that are used for producing the results of the paper. I was wondering if you could provide instruction on how to apply your code or pre-trained model to our own datasets.

Hello

Thanks for sharing your file. I am facing an issue while downloading OpenImages dataset 2018. I have prepared and downloaded all the required files from OpenImages offical Website. But facing this issue can you please share its [solution.]

We knonw that in line 67-68 of 'NUS_WIDE_rank_Visual_Word_Attention.py', 'pickle.load(infile)[1]' means the word vectors of unseen classes.

So, i am a little confused why do you only use unseen classes when training the attention?

Thank you for sharing the useful code.
I have a question about augmenting 1 in attention function in model_share_attention.py. I don't understand the significance of augmenting one or augmenting zero in training. These calculations are also not mentioned in the paper.

Hi @hbdat,

I was trying to train the open-images dataset but I was not able to find the evaluate function for the same.
I also wanted to ask, the training images are taken from 5 million images with trainable classes?

Regards,
Akshita

Hello @hbdat,

Hope you are doing great, I was trying to download the open-images dataset but there is no annotations-human.csv file available in 2017_11 folder. It would be really helpful if you could share the file 😄