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PySlowFast Model Zoo and Baselines

Kinetics

We provided original pretrained models from Caffe2 on heavy models (testing Caffe2 pretrained model in PyTorch might have a small different in performance):

architecture depth pretrain frame length x sample rate top1 top5 model config
C2D R50 - 8 x 8 67.2 87.8 link Kinetics/c2/C2D_NOPOOL_8x8_R50
I3D R50 - 8 x 8 73.5 90.8 link Kinetics/c2/I3D_8x8_R50
I3D NLN R50 - 8 x 8 74.0 91.1 link Kinetics/c2/I3D_NLN_8x8_R50
Slow R50 - 4 x 16 72.7 90.3 link Kinetics/c2/SLOW_4x16_R50
Slow R50 - 8 x 8 74.8 91.6 link Kinetics/c2/SLOW_8x8_R50
SlowFast R50 - 4 x 16 75.6 92.0 link Kinetics/c2/SLOWFAST_4x16_R50
SlowFast R50 - 8 x 8 77.0 92.6 link Kinetics/c2/SLOWFAST_8x8_R50
SlowFast R101 - 8 x 8 78.0 93.3 link Kinetics/c2/SLOWFAST_8x8_R101_101_101
SlowFast R101 - 16 x 8 78.9 93.5 link Kinetics/c2/SLOWFAST_16x8_R101_50_50

X3D models (details in projects/x3d)

architecture size pretrain frame length x sample rate top1 10-view top1 30-view parameters (M) FLOPs (G) model config
X3D XS - 4 x 12 68.7 69.5 3.8 0.60 link Kinetics/X3D_XS
X3D S - 13 x 6 73.1 73.5 3.8 1.96 link Kinetics/X3D_S
X3D M - 16 x 5 75.1 76.2 3.8 4.73 link Kinetics/X3D_M
X3D L - 16 x 5 76.9 77.5 6.2 18.37 link Kinetics/X3D_L

AVA

architecture depth Pretrain Model frame length x sample rate MAP AVA version model
Slow R50 Kinetics 400 4 x 16 19.5 2.2 link
SlowFast R101 Kinetics 600 8 x 8 28.2 2.1 link
SlowFast R101 Kinetics 600 8 x 8 29.1 2.2 link
SlowFast R101 Kinetics 600 16 x 8 29.4 2.2 link

Multigrid Training

Update June, 2020: In the following we provide (reimplemented) models from "A Multigrid Method for Efficiently Training Video Models " paper. The multigrid method trains about 3-6x faster than the original training on multiple datasets. See projects/multigrid for more information. The following provides models, results, and example config files.

Kinetics:

architecture depth pretrain frame length x sample rate training top1 top5 model config
SlowFast R50 - 8 x 8 Standard 76.8 92.7 link Kinetics/SLOWFAST_8x8_R50_stepwise
SlowFast R50 - 8 x 8 Multigrid 76.6 92.7 link Kinetics/SLOWFAST_8x8_R50_stepwise_multigrid

(Here we use stepwise learning rate schedule.)

Something-Something V2:

architecture depth pretrain frame length x sample rate training top1 top5 model config
SlowFast R50 Kinetics 400 16 x 8 Standard 63.0 88.5 link SSv2/SLOWFAST_16x8_R50
SlowFast R50 Kinetics 400 16 x 8 Multigrid 63.5 88.7 link SSv2/SLOWFAST_16x8_R50_multigrid

Charades

architecture depth pretrain frame length x sample rate training mAP model config
SlowFast R50 Kinetics 400 16 x 8 Standard 38.9 link SSv2/SLOWFAST_16x8_R50
SlowFast R50 Kinetics 400 16 x 8 Multigrid 38.6 link SSv2/SLOWFAST_16x8_R50_multigrid

ImageNet

We also release the imagenet pretrained model if finetuning from ImageNet is preferred. The reported accuracy is obtained by center crop testing on the validation set.

architecture depth Top1 Top5 model
ResNet R50 23.6 6.8 link