GT-Vision-Lab/VQA_LSTM_CNN
Train a deeper LSTM and normalized CNN Visual Question Answering model. This current code can get 58.16 on OpenEnded and 63.09 on Multiple-Choice on test-standard.
Lua
Issues
- 2
- 0
How to process the multiple choice answer
#35 opened by WangWenshan - 0
Abstract scene parameters num_ans and num_output
#34 opened by sanjass - 0
UNk Token
#33 opened by samarIbrahem - 1
Unsupported marker type 0xf0
#30 opened by woshiacai - 0
out of memory
#31 opened by woshiacai - 1
- 0
Number of pretrained image features not matching with number of images in COCO
#29 opened by franroldans - 2
Trained model gets low accuracy on VQA server
#28 opened by idansc - 0
- 0
Providing feedback through correct answer
#25 opened by goodrahstar - 0
- 1
- 4
- 2
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setting for abstract?
#22 opened by shinandrew - 3
- 0
require 'cunn' and 'cutorch' in CPU mode
#19 opened by NightFury13 - 0
Number of training picture
#17 opened by andrewliao11 - 3
How to cite the model?
#16 opened by ili3p - 16
- 2
run prepro_img.lua failed
#11 opened by andyyuan78 - 1
- 1
th train.lua -backend nn failed!
#10 opened by andyyuan78 - 1
JPG is actually a PNG
#8 opened by nhynes - 1
- 6