lldan

@Toolazy2cruel did you solve it? i have the same problem

thank you for your reply, Is the implementation method the same on the V-COCO and HICO data sets? I am not very familiar with tensorflow, and I have not found...

@zhihou7 hi，Can this model be run based on resnet50? In download_dataset.sh，there is only a download link for resnet50, but in the FCL project, the model is trained based on resnet101.

@zhihou7 Sorry to bother you again, in Fabricator.py var_fabricate_gen_lite(), Why is this function(convert_emb_feats) called twice?Looking forward to your reply

 Sorry to bother you again. Is your obj embedding randomly generated? Corresponding to "word2vec_list" in the code, the dimension is verb*obj_num_class*2048

@cloudtoro have you sovle this problem? I hava the same problem.

Hi, In you forked repositories, how to get train_sents_gt.txt and test_sents_gt.txt, val_sents_gt.txt

@meteora9479 Hi, In you forked repositories ,how to get train_sents_gt.txt and test_sents_gt.txt,vali_sents_gt.txt?

@zxczrx123 thanks，I have found this problem, and there is one more point to pay attention to, the parameter num_vec needs to be increased

@zxczrx123 Yes, when I increase the data range, many category indicators have dropped significantly. I have not found a better way except to increase the parameter num_vec。