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The official Codes for NeurIPS 2019 paper. Quanfu Fan, Ricarhd Chen, Hilde Kuehne, Marco Pistoia, David Cox, "More Is Less: Learning Efficient Video Representations by Temporal Aggregation Modules"

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Thank you very much for posting the codebase! However, I'm having difficulty replicating the 71.0% acc mentioned in the paper for 'bLVNet-TAM-8×2', I only get around 55% when validating each...

Thanks for your excellent work! I tried to train a bLVNet-101-TAM-a2-b4-f8x2 model on Something-Something V1 using the hyperparameters setting reflected in the following bash command: CUDA_VISIBLE_DEVICES=0,1 python train.py --datadir /media/data/something_v1...

I am doing 2 class classification using BLVNET-TAM. When i had given data for validation the accuracy is coming good but on testing same data accuracy is bad. for instance...