Acc1 about training HMDB51 pretrained on Imagenet about temporal-shift-module HOT 5 CLOSED

this is my command

python -u main.py hmdb51 RGB --arch resnet50 --num_segments 8 --gd 20 --lr 0.001 --lr_steps 10 20 --epochs 25 --batch-size 8 -j 8 --dropout 0.8 --consensus_type=avg --eval-freq=1 --shift --shift_div=8 --shift_place=blockres > log.log

from temporal-shift-module.

same here, maximum 51% acc for 50 epochs at [20, 40] decay.

from temporal-shift-module.

@VanChilly I think the result are obtained by a pre-trained model from K400 then finetune on HMDB

from temporal-shift-module.

same here, maximum 51% acc for 50 epochs at [20, 40] decay.

So, it's clear that the result is reasonable for HMDB pre-trained on ImageNet. 👍

from temporal-shift-module.

@VanChilly I think the result are obtained by a pre-trained model from K400 then finetune on HMDB

Yeah, the author mentioned that in the paper. Thank you.

from temporal-shift-module.