深度学习入门(7) - Video Understanding

Videos

Due to the memory constraints, we have to do some down-sampling

Raw video: long high fps

Training: short clips with low fps

testing: run model on different clips, averaging predictions

Single-frame CNN

train normal 2D CNN to classify frames independently!

easy but a very strong baseline!

Late fusion

take the time axis into account

(flatten / average pooling) concatenate the results of CNNs and feed to MLP to get a classification score

Problem: Hard to compare low-level motion between frames

Early Fusion

compare frames with very first conv layer after that normal 2D CNN

then pass a 2D CNN to get class score

Problem: only one layer of the temporal processing may be not enough

3D CNN (slow fusion n