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code for "SUPPORT-SET BASED MULTI-MODAL REPRESENTATION ENHANCEMENT FOR VIDEO CAPTIONING"(ICME2022) image

dependencies

torch 1.8.1

torchtext 0.9.1

torchvision 0.9.1

python 3.6.9

Data

You need to download the following files to reproduce the experiments

caption-eval & features & text files & Bert related files:

LINK:https://pan.baidu.com/s/13SQdmq0iDHJA2-bcwcDk2A

PASSWORD:icme

checkpoint:

MSVD*******

Bleu_1: 84.545195

Bleu_2: 74.130214

Bleu_3: 64.860649

Bleu_4: 55.485736

METEOR: 35.952250

ROUGE_L: 73.029840

CIDEr: 96.142574


LINK:https://pan.baidu.com/s/13kJ32N-C4pkIE-Dlst05zA

PASSWORD:icme

Train

You can train the model by running the following command:

sh train.sh

Evaluation

python evaluate.py --dataset=msvd --model=RMN \
 --result_dir=results/xxxx --attention=soft \
 --hidden_size=1024 --att_size=1024 \
 --test_batch_size=32 --beam_size=5 \
 --eval_metric=CIDEr --topk=18 --max_words=26

Acknowledgement

This repository is partly built based on Ganchao Tan's RMN(https://github.com/tgc1997/RMN) for video captioning.

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