1. The **gpus** indicates the number of gpu we used to get the checkpoint. It is noteworthy that the configs we provide are used for 8 gpus as default.
...
...
@@ -44,7 +47,7 @@ Example: test I3D model on Kinetics-400 dataset and dump the result to a json fi
In data benchmark, we compare two different data preprocessing methods: (1) Resize video to 340x256, (2) Resize the short edge of video to 320px.
In data benchmark, we compare two different data preprocessing methods: (1) Resize video to 340x256, (2) Resize the short edge of video to 320px, (3) Resize the short edge of video to 256px.
|tsn_r50_320p_1x1x8_kinetics400_twostream [1: 1]* |x|x| ResNet50| ImageNet |74.64|91.77| x | x | x | x | x|x|x|
...
...
@@ -28,7 +30,10 @@ Here, We use [1: 1] to indicate that we combine rgb and flow score with coeffici
### Kinetics-400 Data Benchmark (8-gpus, ResNet50, ImageNet pretrain; 3 segments)
In data benchmark, we compare: 1. Different data preprocessing methods: (1) Resize video to 340x256, (2) Resize the short edge of video to 320px; 2. Different data augmentation methods: (1) MultiScaleCrop, (2) RandomResizedCrop; 3. Different testing protocols: (1) 25 frames x 10 crops, (2) 25 frames x 3 crops.
In data benchmark, we compare:
1. Different data preprocessing methods: (1) Resize video to 340x256, (2) Resize the short edge of video to 320px, (3) Resize the short edge of video to 256px;
2. Different data augmentation methods: (1) MultiScaleCrop, (2) RandomResizedCrop;
3. Different testing protocols: (1) 25 frames x 10 crops, (2) 25 frames x 3 crops.