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

评论
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值