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resnet_50_train_val
dfbbba6b
·
merging scripts and modifications for train + val training
·
Mar 11, 2017
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acc_vs_qa_rarity
397ecc10
·
constants_crunchy update
·
Nov 11, 2016
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acc_vs_ratio
8c12860b
·
change accuracy to top-20 instead of top-100
·
Nov 09, 2016
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rel_bin_feats
3ee92ab0
·
constants_crunchy update
·
Nov 09, 2016
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extract_word_vectors
95bf6bfb
·
extract word vectors
·
Nov 08, 2016
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no_single_feats_pretrained
2c4d564e
·
add new constants_crunchy
·
Nov 07, 2016
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no_single_feats_discon
43a6c906
·
noun adj identity and yes_no_num in ans eval
·
Nov 06, 2016
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single_features
22de2cfa
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eval_interpret
·
Nov 01, 2016
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no_single_feats
69cfa30c
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constants_vision_gpu_1 update
·
Oct 29, 2016
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simple_avg_reg_feat
f07ae542
·
add yes no feat in select best model
·
Oct 24, 2016
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add_test_eval
5f99cf5b
·
add paths for vqa test and testdev and add eval scripts for them
·
Oct 24, 2016
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use_margin_mil_loss
96d4d23e
·
constants_crunchy no major change
·
Oct 21, 2016
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backup_simple_avg_reg_feat
c9c1b754
·
the architecture that gives 64 overall accuracy
·
Oct 21, 2016
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bn_before_feat_add
ade442ce
·
answer inference first transforms then bn then add different feat
·
Oct 19, 2016
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use_detector_scores
610ac1fc
·
changed the region relevance back to original
·
Oct 19, 2016
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discon_wordvec_classifiers
3862a0bd
·
disconnect word vectors and obj/atr classifiers
·
Oct 17, 2016
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avg_reg_feats
49a622c1
·
use averaged region features instead of averaging prob
·
Oct 13, 2016
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fix_genome_split
2bb5fc27
·
constants_vision_gpu_2
·
Oct 10, 2016
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GenVQA_obj_atr_ans_mil
6131e519
·
GenVQA_obj_atr_ans_mil
·
Oct 04, 2016
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inner_product_selection
adfc0ab6
·
make ans eval and train compatible with each other
·
Oct 04, 2016
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