Comments (3)
We used the pretrained I3D model on Kinetics. Then we used a window of size 21 around each frame, i.e. [t-10, t+10] to extract frame-wise features. For more details about the features please check this repo https://github.com/ahsaniqbal/Kinetics-FeatureExtractor
from asformer.
So, considering a stack size (or window size) of 21, the extracted features will have size (n_frames / 21) x 1024, right? (which then, by concatenating the stram RGB and flow will become (n_frames / 64) * 2048). Didn't you use any step between one window and another? Sorry for the many questions, but I'm really curious and I really want to use this model!
from asformer.
Sorry for my late response :) really got some busy days. We do not use any step between windows since we have to collect features per-frame with full fps rate.
from asformer.
Related Issues (17)
- cross-self attention HOT 1
- about the randomness of code HOT 1
- Error in evaluation code HOT 2
- Enviroment issues HOT 1
- The provided models generate lower scores than the paper reported HOT 3
- How to understand stage images from result HOT 6
- How to extract attention weights HOT 4
- Issue while trying to run the pretained models.
- attention实现的问题 HOT 5
- flops,GPU mem code HOT 4
- Long training time HOT 2
- Batch size constraint HOT 6
- Cannot download the model HOT 2
- pre-extracted feature HOT 1
- results on salads50 does not match table 5 HOT 3
- Increase the batchsize and the result is hurt HOT 2
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from asformer.