Collections: - Name: TSM README: configs/recognition/tsm/README.md Paper: URL: https://arxiv.org/abs/1811.08383 Title: "TSM: Temporal Shift Module for Efficient Video Understanding" Models: - Config: configs/recognition/tsm/tsm_r50_1x1x8_50e_kinetics400_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 8 Epochs: 50 FLOPs: 32965562368 Parameters: 24327632 Pretrained: ImageNet Resolution: 340x256 Training Data: Kinetics-400 Training Resources: 8 GPUs Modality: RGB Name: tsm_r50_1x1x8_50e_kinetics400_rgb Results: - Dataset: Kinetics-400 Metrics: Top 1 Accuracy: 70.24 Top 5 Accuracy: 89.56 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x8_50e_kinetics400_rgb/20200607_211800.log.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x8_50e_kinetics400_rgb/20200607_211800.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x8_50e_kinetics400_rgb/tsm_r50_1x1x8_50e_kinetics400_rgb_20200607-af7fb746.pth - Config: configs/recognition/tsm/tsm_r50_1x1x8_50e_kinetics400_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 8 Epochs: 50 FLOPs: 32965562368 Parameters: 24327632 Pretrained: ImageNet Resolution: short-side 256 Training Data: Kinetics-400 Training Resources: 8 GPUs Modality: RGB Name: tsm_r50_1x1x8_50e_kinetics400_rgb Results: - Dataset: Kinetics-400 Metrics: Top 1 Accuracy: 70.59 Top 5 Accuracy: 89.52 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_256p_1x1x8_50e_kinetics400_rgb/20200725_031623.log.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_256p_1x1x8_50e_kinetics400_rgb/20200725_031623.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_256p_1x1x8_50e_kinetics400_rgb/tsm_r50_256p_1x1x8_50e_kinetics400_rgb_20200726-020785e2.pth - Config: configs/recognition/tsm/tsm_r50_1x1x8_50e_kinetics400_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 8 Epochs: 50 FLOPs: 32965562368 Parameters: 24327632 Pretrained: ImageNet Resolution: short-side 320 Training Data: Kinetics-400 Training Resources: 8 GPUs Modality: RGB Name: tsm_r50_1x1x8_50e_kinetics400_rgb Results: - Dataset: Kinetics-400 Metrics: Top 1 Accuracy: 70.73 Top 5 Accuracy: 89.81 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x8_50e_kinetics400_rgb/20210616_021451.log.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x8_50e_kinetics400_rgb/20210616_021451.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x8_50e_kinetics400_rgb/tsm_r50_1x1x8_50e_kinetics400_rgb_20210701-68d582b4.pth - Config: configs/recognition/tsm/tsm_r50_1x1x8_100e_kinetics400_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 8 Epochs: 100 FLOPs: 32965562368 Parameters: 24327632 Pretrained: ImageNet Resolution: short-side 320 Training Data: Kinetics-400 Training Resources: 8 GPUs Modality: RGB Name: tsm_r50_1x1x8_100e_kinetics400_rgb Results: - Dataset: Kinetics-400 Metrics: Top 1 Accuracy: 71.9 Top 5 Accuracy: 90.03 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x8_100e_kinetics400_rgb/20210617_103543.log.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x8_100e_kinetics400_rgb/20210617_103543.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x8_100e_kinetics400_rgb/tsm_r50_1x1x8_100e_kinetics400_rgb_20210701-7ff22268.pth - Config: configs/recognition/tsm/tsm_r50_gpu_normalize_1x1x8_50e_kinetics400_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 8 Epochs: 50 FLOPs: 32965562368 Parameters: 24327632 Pretrained: ImageNet Resolution: short-side 256 Training Data: Kinetics-400 Training Resources: 8 GPUs Modality: RGB Name: tsm_r50_gpu_normalize_1x1x8_50e_kinetics400_rgb Results: - Dataset: Kinetics-400 Metrics: Top 1 Accuracy: 70.48 Top 5 Accuracy: 89.4 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_gpu_normalize_1x1x8_50e_kinetics400_rgb/tsm_r50_gpu_normalize_1x1x8_50e_kinetics400_rgb_20210219.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_gpu_normalize_1x1x8_50e_kinetics400_rgb/tsm_r50_gpu_normalize_1x1x8_50e_kinetics400_rgb_20210219.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_gpu_normalize_1x1x8_50e_kinetics400_rgb/tsm_r50_gpu_normalize_1x1x8_50e_kinetics400_rgb_20210219-bf96e6cc.pth - Config: configs/recognition/tsm/tsm_r50_video_1x1x8_50e_kinetics400_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 8 Epochs: 50 FLOPs: 32965562368 Parameters: 24327632 Pretrained: ImageNet Resolution: short-side 256 Training Data: Kinetics-400 Training Resources: 8 GPUs Modality: RGB Name: tsm_r50_video_1x1x8_50e_kinetics400_rgb Results: - Dataset: Kinetics-400 Metrics: Top 1 Accuracy: 70.25 Top 5 Accuracy: 89.66 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_video_1x1x8_100e_kinetics400_rgb/tsm_r50_video_2d_1x1x8_50e_kinetics400_rgb.log.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_video_1x1x8_100e_kinetics400_rgb/tsm_r50_video_2d_1x1x8_50e_kinetics400_rgb.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_video_1x1x8_100e_kinetics400_rgb/tsm_r50_video_1x1x8_100e_kinetics400_rgb_20200702-a77f4328.pth - Config: configs/recognition/tsm/tsm_r50_dense_1x1x8_50e_kinetics400_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 8 Epochs: 50 FLOPs: 32965562368 Parameters: 24327632 Pretrained: ImageNet Resolution: short-side 320 Training Data: Kinetics-400 Training Resources: 8 GPUs Modality: RGB Name: tsm_r50_dense_1x1x8_50e_kinetics400_rgb Results: - Dataset: Kinetics-400 Metrics: Top 1 Accuracy: 73.46 Top 5 Accuracy: 90.84 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_dense_1x1x8_50e_kinetics400_rgb/20210617_103245.log.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_dense_1x1x8_50e_kinetics400_rgb/20210617_103245.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_dense_1x1x8_50e_kinetics400_rgb/tsm_r50_dense_1x1x8_50e_kinetics400_rgb_20210701-a54ff3d3.pth - Config: configs/recognition/tsm/tsm_r50_dense_1x1x8_100e_kinetics400_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 8 Epochs: 100 FLOPs: 32965562368 Parameters: 24327632 Pretrained: ImageNet Resolution: short-side 320 Training Data: Kinetics-400 Training Resources: 8 GPUs Modality: RGB Name: tsm_r50_dense_1x1x8_100e_kinetics400_rgb Results: - Dataset: Kinetics-400 Metrics: Top 1 Accuracy: 74.55 Top 5 Accuracy: 91.74 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_dense_1x1x8_100e_kinetics400_rgb/20210613_034931.log.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_dense_1x1x8_100e_kinetics400_rgb/20210613_034931.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_dense_1x1x8_100e_kinetics400_rgb/tsm_r50_dense_1x1x8_100e_kinetics400_rgb_20210701-e3e5e97f.pth - Config: configs/recognition/tsm/tsm_r50_1x1x16_50e_kinetics400_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 6 Epochs: 50 FLOPs: 65931124736 Parameters: 24327632 Pretrained: ImageNet Resolution: 340x256 Training Data: Kinetics-400 Training Resources: 8 GPUs Modality: RGB Name: tsm_r50_1x1x16_50e_kinetics400_rgb Results: - Dataset: Kinetics-400 Metrics: Top 1 Accuracy: 72.09 Top 5 Accuracy: 90.37 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x16_50e_kinetics400_rgb/20201011_205356.log.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x16_50e_kinetics400_rgb/20201011_205356.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x16_50e_kinetics400_rgb/tsm_r50_340x256_1x1x16_50e_kinetics400_rgb_20201011-2f27f229.pth - Config: configs/recognition/tsm/tsm_r50_1x1x16_50e_kinetics400_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 6 Epochs: 50 FLOPs: 65931124736 Parameters: 24327632 Pretrained: ImageNet Resolution: short-side 256 Training Data: Kinetics-400 Training Resources: 32 GPUs Modality: RGB Name: tsm_r50_1x1x16_50e_kinetics400_rgb Results: - Dataset: Kinetics-400 Metrics: Top 1 Accuracy: 71.89 Top 5 Accuracy: 90.73 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_256p_1x1x16_50e_kinetics400_rgb/20201010_224825.log.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_256p_1x1x16_50e_kinetics400_rgb/20201010_224825.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_256p_1x1x16_50e_kinetics400_rgb/tsm_r50_256p_1x1x16_50e_kinetics400_rgb_20201010-85645c2a.pth - Config: configs/recognition/tsm/tsm_r50_1x1x16_100e_kinetics400_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 6 Epochs: 100 FLOPs: 65931124736 Parameters: 24327632 Pretrained: ImageNet Resolution: short-side 320 Training Data: Kinetics-400 Training Resources: 8 GPUs Modality: RGB Name: tsm_r50_1x1x16_100e_kinetics400_rgb Results: - Dataset: Kinetics-400 Metrics: Top 1 Accuracy: 72.80 Top 5 Accuracy: 90.75 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x16_50e_kinetics400_rgb/20210621_115844.log.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x16_50e_kinetics400_rgb/20210621_115844.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x16_50e_kinetics400_rgb/tsm_r50_1x1x16_50e_kinetics400_rgb_20210701-7c0c5d54.pth - Config: configs/recognition/tsm/tsm_nl_embedded_gaussian_r50_1x1x8_50e_kinetics400_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 8 Epochs: 50 FLOPs: 49457811456 Parameters: 31682000 Pretrained: ImageNet Resolution: short-side 320 Training Data: Kinetics-400 Training Resources: 32 GPUs Modality: RGB Name: tsm_nl_embedded_gaussian_r50_1x1x8_50e_kinetics400_rgb Results: - Dataset: Kinetics-400 Metrics: Top 1 Accuracy: 72.03 Top 5 Accuracy: 90.25 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_nl_embedded_gaussian_r50_1x1x8_50e_kinetics400_rgb/20200724_120023.log.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_nl_embedded_gaussian_r50_1x1x8_50e_kinetics400_rgb/20200724_120023.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_nl_embedded_gaussian_r50_1x1x8_50e_kinetics400_rgb/tsm_nl_embedded_gaussian_r50_1x1x8_50e_kinetics400_rgb_20200724-f00f1336.pth - Config: configs/recognition/tsm/tsm_nl_gaussian_r50_1x1x8_50e_kinetics400_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 8 Epochs: 50 FLOPs: 41231355904 Parameters: 28007888 Pretrained: ImageNet Resolution: short-side 320 Training Data: Kinetics-400 Training Resources: 32 GPUs Modality: RGB Name: tsm_nl_gaussian_r50_1x1x8_50e_kinetics400_rgb Results: - Dataset: Kinetics-400 Metrics: Top 1 Accuracy: 70.7 Top 5 Accuracy: 89.9 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_nl_gaussian_r50_1x1x8_50e_kinetics400_rgb/20200815_210253.log.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_nl_gaussian_r50_1x1x8_50e_kinetics400_rgb/20200815_210253.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_nl_gaussian_r50_1x1x8_50e_kinetics400_rgb/tsm_nl_gaussian_r50_1x1x8_50e_kinetics400_rgb_20200816-b93fd297.pth - Config: configs/recognition/tsm/tsm_nl_dot_product_r50_1x1x8_50e_kinetics400_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 8 Epochs: 50 FLOPs: 49457811456 Parameters: 31682000 Pretrained: ImageNet Resolution: short-side 320 Training Data: Kinetics-400 Training Resources: 32 GPUs Modality: RGB Name: tsm_nl_dot_product_r50_1x1x8_50e_kinetics400_rgb Results: - Dataset: Kinetics-400 Metrics: Top 1 Accuracy: 71.6 Top 5 Accuracy: 90.34 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_nl_dot_product_r50_1x1x8_50e_kinetics400_rgb/20200723_220442.log.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_nl_dot_product_r50_1x1x8_50e_kinetics400_rgb/20200723_220442.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_nl_dot_product_r50_1x1x8_50e_kinetics400_rgb/tsm_nl_dot_product_r50_1x1x8_50e_kinetics400_rgb_20200724-d8ad84d2.pth - Config: configs/recognition/tsm/tsm_mobilenetv2_dense_1x1x8_100e_kinetics400_rgb.py In Collection: TSM Metadata: Architecture: MobileNetV2 Batch Size: 8 Epochs: 100 FLOPs: 3337519104 Parameters: 2736272 Pretrained: ImageNet Resolution: short-side 320 Training Data: Kinetics-400 Training Resources: 8 GPUs Modality: RGB Name: tsm_mobilenetv2_dense_1x1x8_100e_kinetics400_rgb Results: - Dataset: Kinetics-400 Metrics: Top 1 Accuracy: 68.46 Top 5 Accuracy: 88.64 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_mobilenetv2_dense_1x1x8_100e_kinetics400_rgb/20210129_024936.log.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_mobilenetv2_dense_1x1x8_100e_kinetics400_rgb/20210129_024936.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_mobilenetv2_dense_1x1x8_100e_kinetics400_rgb/tsm_mobilenetv2_dense_320p_1x1x8_100e_kinetics400_rgb_20210202-61135809.pth - Config: configs/recognition/tsm/tsm_r50_video_1x1x8_50e_diving48_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 8 Epochs: 50 FLOPs: 32959795200 Parameters: 23606384 Pretrained: ImageNet Training Data: Diving48 Training Resources: 8 GPUs Modality: RGB Name: tsm_r50_video_1x1x8_50e_diving48_rgb Results: - Dataset: Diving48 Metrics: Top 1 Accuracy: 75.99 Top 5 Accuracy: 97.16 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_video_1x1x8_50e_diving48_rgb/20210426_012424.log.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_video_1x1x8_50e_diving48_rgb/20210426_012424.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_video_1x1x8_50e_diving48_rgb/tsm_r50_video_1x1x8_50e_diving48_rgb_20210426-aba5aa3d.pth - Config: configs/recognition/tsm/tsm_r50_video_1x1x16_50e_diving48_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 4 Epochs: 50 FLOPs: 65919590400 Parameters: 23606384 Pretrained: ImageNet Training Data: Diving48 Training Resources: 8 GPUs Modality: RGB Name: tsm_r50_video_1x1x16_50e_diving48_rgb Results: - Dataset: Diving48 Metrics: Top 1 Accuracy: 81.62 Top 5 Accuracy: 97.66 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_video_1x1x16_50e_diving48_rgb/20210426_012823.log.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_video_1x1x16_50e_diving48_rgb/20210426_012823.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_video_1x1x16_50e_diving48_rgb/tsm_r50_video_1x1x16_50e_diving48_rgb_20210426-aa9631c0.pth - Config: configs/recognition/tsm/tsm_r50_1x1x8_50e_sthv1_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 8 Epochs: 50 FLOPs: 32961859584 Parameters: 23864558 Pretrained: ImageNet Resolution: height 100 Training Data: SthV1 Training Resources: 8 GPUs Modality: RGB Name: tsm_r50_1x1x8_50e_sthv1_rgb Results: - Dataset: SthV1 Metrics: Top 1 Accuracy: 47.7 Top 1 Accuracy (efficient): 45.58 Top 5 Accuracy: 76.12 Top 5 Accuracy (efficient): 75.02 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x8_50e_sthv1_rgb/20210203_150227.log.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x8_50e_sthv1_rgb/20210203_150227.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x8_50e_sthv1_rgb/tsm_r50_1x1x8_50e_sthv1_rgb_20210203-01dce462.pth reference top1 acc (efficient/accurate): '[45.50 / 47.33](https://github.com/mit-han-lab/temporal-shift-module/tree/8d53d6fda40bea2f1b37a6095279c4b454d672bd#training)' reference top5 acc (efficient/accurate): '[74.34 / 76.60](https://github.com/mit-han-lab/temporal-shift-module/tree/8d53d6fda40bea2f1b37a6095279c4b454d672bd#training)' - Config: configs/recognition/tsm/tsm_r50_flip_1x1x8_50e_sthv1_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 8 Epochs: 50 FLOPs: 32961859584 Parameters: 23864558 Pretrained: ImageNet Resolution: height 100 Training Data: SthV1 Training Resources: 8 GPUs Modality: RGB Name: tsm_r50_flip_1x1x8_50e_sthv1_rgb Results: - Dataset: SthV1 Metrics: Top 1 Accuracy: 48.51 Top 1 Accuracy (efficient): 47.1 Top 5 Accuracy: 77.56 Top 5 Accuracy (efficient): 76.02 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_flip_1x1x8_50e_sthv1_rgb/20210203_145829.log.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_flip_1x1x8_50e_sthv1_rgb/20210203_145829.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_flip_1x1x8_50e_sthv1_rgb/tsm_r50_flip_1x1x8_50e_sthv1_rgb_20210203-12596f16.pth reference top1 acc (efficient/accurate): '[45.50 / 47.33](https://github.com/mit-han-lab/temporal-shift-module/tree/8d53d6fda40bea2f1b37a6095279c4b454d672bd#training)' reference top5 acc (efficient/accurate): '[74.34 / 76.60](https://github.com/mit-han-lab/temporal-shift-module/tree/8d53d6fda40bea2f1b37a6095279c4b454d672bd#training)' - Config: configs/recognition/tsm/tsm_r50_randaugment_1x1x8_50e_sthv1_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 8 Epochs: 50 FLOPs: 32961859584 Parameters: 23864558 Pretrained: ImageNet Resolution: height 100 Training Data: SthV1 Training Resources: 8 GPUs Modality: RGB Name: tsm_r50_randaugment_1x1x8_50e_sthv1_rgb Results: - Dataset: SthV1 Metrics: Top 1 Accuracy: 48.9 Top 1 Accuracy (efficient): 47.16 Top 5 Accuracy: 77.92 Top 5 Accuracy (efficient): 76.07 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_randaugment_1x1x8_50e_sthv1_rgb/tsm_r50_randaugment_1x1x8_50e_sthv1_rgb.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_randaugment_1x1x8_50e_sthv1_rgb/tsm_r50_randaugment_1x1x8_50e_sthv1_rgb.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_randaugment_1x1x8_50e_sthv1_rgb/tsm_r50_randaugment_1x1x8_50e_sthv1_rgb_20210324-481268d9.pth reference top1 acc (efficient/accurate): '[45.50 / 47.33](https://github.com/mit-han-lab/temporal-shift-module/tree/8d53d6fda40bea2f1b37a6095279c4b454d672bd#training)' reference top5 acc (efficient/accurate): '[74.34 / 76.60](https://github.com/mit-han-lab/temporal-shift-module/tree/8d53d6fda40bea2f1b37a6095279c4b454d672bd#training)' - Config: configs/recognition/tsm/tsm_r50_flip_randaugment_1x1x8_50e_sthv1_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 8 Epochs: 50 FLOPs: 32961859584 Parameters: 23864558 Pretrained: ImageNet Resolution: height 100 Training Data: SthV1 Training Resources: 8 GPUs Modality: RGB Name: tsm_r50_flip_randaugment_1x1x8_50e_sthv1_rgb Results: - Dataset: SthV1 Metrics: Top 1 Accuracy: 50.31 Top 1 Accuracy (efficient): 47.85 Top 5 Accuracy: 78.18 Top 5 Accuracy (efficient): 76.78 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_flip_randaugment_1x1x8_50e_sthv1_rgb/tsm_r50_flip_randaugment_1x1x8_50e_sthv1_rgb.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_flip_randaugment_1x1x8_50e_sthv1_rgb/tsm_r50_flip_randaugment_1x1x8_50e_sthv1_rgb.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_flip_randaugment_1x1x8_50e_sthv1_rgb/tsm_r50_flip_randaugment_1x1x8_50e_sthv1_rgb_20210324-76937692.pth reference top1 acc (efficient/accurate): '[45.50 / 47.33](https://github.com/mit-han-lab/temporal-shift-module/tree/8d53d6fda40bea2f1b37a6095279c4b454d672bd#training)' reference top5 acc (efficient/accurate): '[74.34 / 76.60](https://github.com/mit-han-lab/temporal-shift-module/tree/8d53d6fda40bea2f1b37a6095279c4b454d672bd#training)' - Config: configs/recognition/tsm/tsm_r50_1x1x16_50e_sthv1_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 6 Epochs: 50 FLOPs: 65923719168 Parameters: 23864558 Pretrained: ImageNet Resolution: height 100 Training Data: SthV1 Training Resources: 8 GPUs Modality: RGB Name: tsm_r50_1x1x16_50e_sthv1_rgb Results: - Dataset: SthV1 Metrics: Top 1 Accuracy: 49.03 Top 1 Accuracy (efficient): 47.77 Top 5 Accuracy: 77.83 Top 5 Accuracy (efficient): 76.82 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x16_50e_sthv1_rgb/tsm_r50_1x1x16_50e_sthv1_rgb.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x16_50e_sthv1_rgb/tsm_r50_1x1x16_50e_sthv1_rgb.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x16_50e_sthv1_rgb/tsm_r50_1x1x16_50e_sthv1_rgb_20211202-b922e5d2.pth reference top1 acc (efficient/accurate): '[47.05 / 48.61](https://github.com/mit-han-lab/temporal-shift-module/tree/8d53d6fda40bea2f1b37a6095279c4b454d672bd#training)' reference top5 acc (efficient/accurate): '[76.40 / 77.96](https://github.com/mit-han-lab/temporal-shift-module/tree/8d53d6fda40bea2f1b37a6095279c4b454d672bd#training)' - Config: configs/recognition/tsm/tsm_r101_1x1x8_50e_sthv1_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 8 Epochs: 50 FLOPs: 62782459904 Parameters: 42856686 Pretrained: ImageNet Resolution: height 100 Training Data: SthV1 Training Resources: 8 GPUs Modality: RGB Name: tsm_r101_1x1x8_50e_sthv1_rgb Results: - Dataset: SthV1 Metrics: Top 1 Accuracy: 48.59 Top 1 Accuracy (efficient): 46.09 Top 5 Accuracy: 77.10 Top 5 Accuracy (efficient): 75.41 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r101_1x1x8_50e_sthv1_rgb/tsm_r101_1x1x8_50e_sthv1_rgb.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r101_1x1x8_50e_sthv1_rgb/tsm_r101_1x1x8_50e_sthv1_rgb.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r101_1x1x8_50e_sthv1_rgb/tsm_r101_1x1x8_50e_sthv1_rgb_20211202-49970a5b.pth reference top1 acc (efficient/accurate): '[46.64 / 48.13](https://github.com/mit-han-lab/temporal-shift-module/tree/8d53d6fda40bea2f1b37a6095279c4b454d672bd#training)' reference top5 acc (efficient/accurate): '[75.40 / 77.31](https://github.com/mit-han-lab/temporal-shift-module/tree/8d53d6fda40bea2f1b37a6095279c4b454d672bd#training)' - Config: configs/recognition/tsm/tsm_r50_1x1x8_50e_sthv2_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 6 Epochs: 50 FLOPs: 32961859584 Parameters: 23864558 Pretrained: ImageNet Resolution: height 256 Training Data: SthV2 Training Resources: 8 GPUs Modality: RGB Name: tsm_r50_1x1x8_50e_sthv2_rgb Results: - Dataset: SthV2 Metrics: Top 1 Accuracy: 61.82 Top 1 Accuracy (efficient): 59.11 Top 5 Accuracy: 86.80 Top 5 Accuracy (efficient): 85.39 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x8_50e_sthv2_rgb/20210816_224310.log.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x8_50e_sthv2_rgb/20210816_224310.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x8_50e_sthv2_rgb/tsm_r50_256h_1x1x8_50e_sthv2_rgb_20210816-032aa4da.pth reference top1 acc (efficient/accurate): '[57.98 / 60.69](https://github.com/mit-han-lab/temporal-shift-module/tree/8d53d6fda40bea2f1b37a6095279c4b454d672bd#training)' reference top5 acc (efficient/accurate): '[84.57 / 86.28](https://github.com/mit-han-lab/temporal-shift-module/tree/8d53d6fda40bea2f1b37a6095279c4b454d672bd#training)' - Config: configs/recognition/tsm/tsm_r50_1x1x16_50e_sthv2_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 6 Epochs: 50 FLOPs: 32961859584 Parameters: 23864558 Pretrained: ImageNet Resolution: height 256 Training Data: SthV2 Training Resources: 8 GPUs Modality: RGB Name: tsm_r50_1x1x16_50e_sthv2_rgb Results: - Dataset: SthV2 Metrics: Top 1 Accuracy: 63.19 Top 1 Accuracy (efficient): 61.06 Top 5 Accuracy: 87.93 Top 5 Accuracy (efficient): 86.66 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x16_50e_sthv2_rgb/20210331_134458.log.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x16_50e_sthv2_rgb/20210331_134458.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x16_50e_sthv2_rgb/tsm_r50_256h_1x1x16_50e_sthv2_rgb_20210331-0a45549c.pth reference top1 acc (efficient/accurate): '[xx / 63.1](https://github.com/mit-han-lab/temporal-shift-module/tree/8d53d6fda40bea2f1b37a6095279c4b454d672bd#training)' reference top5 acc (efficient/accurate): '[xx / xx](https://github.com/mit-han-lab/temporal-shift-module/tree/8d53d6fda40bea2f1b37a6095279c4b454d672bd#training)' - Config: configs/recognition/tsm/tsm_r101_1x1x8_50e_sthv2_rgb.py In Collection: TSM Metadata: Architecture: ResNet101 Batch Size: 8 Epochs: 50 FLOPs: 62782459904 Parameters: 42856686 Pretrained: ImageNet Resolution: height 256 Training Data: SthV2 Training Resources: 8 GPUs Modality: RGB Name: tsm_r101_1x1x8_50e_sthv2_rgb Results: - Dataset: SthV2 Metrics: Top 1 Accuracy: 63.84 Top 1 Accuracy (efficient): 60.88 Top 5 Accuracy: 88.30 Top 5 Accuracy (efficient): 86.56 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r101_1x1x8_50e_sthv2_rgb/20210401_143656.log.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r101_1x1x8_50e_sthv2_rgb/20210401_143656.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r101_1x1x8_50e_sthv2_rgb/tsm_r101_256h_1x1x8_50e_sthv2_rgb_20210401-df97f3e1.pth reference top1 acc (efficient/accurate): '[xx / 63.3](https://github.com/mit-han-lab/temporal-shift-module/tree/8d53d6fda40bea2f1b37a6095279c4b454d672bd#training)' reference top5 acc (efficient/accurate): '[xx / xx](https://github.com/mit-han-lab/temporal-shift-module/tree/8d53d6fda40bea2f1b37a6095279c4b454d672bd#training)' - Config: configs/recognition/tsm/tsm_r50_mixup_1x1x8_50e_sthv1_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 8 Epochs: 50 FLOPs: 43051352064 Parameters: 23864558 Pretrained: ImageNet Resolution: height 100 Training Data: SthV1 Training Resources: 8 GPUs Modality: RGB Name: tsm_r50_mixup_1x1x8_50e_sthv1_rgb Results: - Dataset: SthV1 Metrics: Top 1 Accuracy: 48.49 Top 1 Accuracy (efficient): 46.35 Top 5 Accuracy: 76.88 Top 5 Accuracy (efficient): 75.07 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_mixup_1x1x8_50e_sthv1_rgb/tsm_r50_mixup_1x1x8_50e_sthv1_rgb.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_mixup_1x1x8_50e_sthv1_rgb/tsm_r50_mixup_1x1x8_50e_sthv1_rgb.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_mixup_1x1x8_50e_sthv1_rgb/tsm_r50_mixup_1x1x8_50e_sthv1_rgb-9eca48e5.pth delta top1 acc (efficient/accurate): +0.77 / +0.79 delta top5 acc (efficient/accurate): +0.05 / +0.70 - Config: configs/recognition/tsm/tsm_r50_cutmix_1x1x8_50e_sthv1_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 8 Epochs: 50 FLOPs: 43051352064 Parameters: 23864558 Pretrained: ImageNet Resolution: height 100 Training Data: SthV1 Training Resources: 8 GPUs Modality: RGB Name: tsm_r50_cutmix_1x1x8_50e_sthv1_rgb Results: - Dataset: SthV1 Metrics: Top 1 Accuracy: 47.46 Top 1 Accuracy (efficient): 45.92 Top 5 Accuracy: 76.71 Top 5 Accuracy (efficient): 75.23 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_cutmix_1x1x8_50e_sthv1_rgb/tsm_r50_cutmix_1x1x8_50e_sthv1_rgb.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_cutmix_1x1x8_50e_sthv1_rgb/tsm_r50_cutmix_1x1x8_50e_sthv1_rgb.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_cutmix_1x1x8_50e_sthv1_rgb/tsm_r50_cutmix_1x1x8_50e_sthv1_rgb-34934615.pth delta top1 acc (efficient/accurate): +0.34 / -0.24 delta top5 acc (efficient/accurate): +0.21 / +0.59 - Config: configs/recognition/tsm/tsm_r50_1x1x8_50e_jester_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 8 Epochs: 50 FLOPs: 43048943616 Parameters: 23563355 Pretrained: ImageNet Resolution: height 100 Training Data: Jester Training Resources: 8 GPUs Modality: RGB Name: tsm_r50_1x1x8_50e_jester_rgb Results: - Dataset: Jester Metrics: Top 1 Accuracy: 97.2 Top 1 Accuracy (efficient): 96.5 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x8_50e_jester_rgb/tsm_r50_1x1x8_50e_jester_rgb.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x8_50e_jester_rgb/tsm_r50_1x1x8_50e_jester_rgb.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x8_50e_jester_rgb/tsm_r50_1x1x8_50e_jester_rgb-c799267e.pth - Config: configs/recognition/tsm/tsm_k400_pretrained_r50_1x1x8_25e_hmdb51_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 12 Epochs: 25 FLOPs: 32959844352 Parameters: 23612531 Pretrained: Kinetics400 Training Data: HMDB51 Training Resources: 8 GPUs Modality: RGB Name: tsm_k400_pretrained_r50_1x1x8_25e_hmdb51_rgb Results: - Dataset: HMDB51 Metrics: Top 1 Accuracy: 72.68 Top 5 Accuracy: 92.03 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_k400_pretrained_r50_1x1x8_25e_hmdb51_rgb/20210605_182554.log.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_k400_pretrained_r50_1x1x8_25e_hmdb51_rgb/20210605_182554.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_k400_pretrained_r50_1x1x8_25e_hmdb51_rgb/tsm_k400_pretrained_r50_1x1x8_25e_hmdb51_rgb_20210630-10c74ee5.pth gpu_mem(M): '10388' - Config: configs/recognition/tsm/tsm_k400_pretrained_r50_1x1x16_25e_hmdb51_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 6 Epochs: 25 FLOPs: 65919688704 Parameters: 23612531 Pretrained: Kinetics400 Training Data: HMDB51 Training Resources: 8 GPUs Modality: RGB Name: tsm_k400_pretrained_r50_1x1x16_25e_hmdb51_rgb Results: - Dataset: HMDB51 Metrics: Top 1 Accuracy: 74.77 Top 5 Accuracy: 93.86 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_k400_pretrained_r50_1x1x16_25e_hmdb51_rgb/20210605_182505.log.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_k400_pretrained_r50_1x1x16_25e_hmdb51_rgb/20210605_182505.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_k400_pretrained_r50_1x1x16_25e_hmdb51_rgb/tsm_k400_pretrained_r50_1x1x16_25e_hmdb51_rgb_20210630-4785548e.pth gpu_mem(M): '10388' - Config: configs/recognition/tsm/tsm_k400_pretrained_r50_1x1x8_25e_ucf101_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 12 Epochs: 25 FLOPs: 32960663552 Parameters: 23714981 Pretrained: Kinetics400 Training Data: UCF101 Training Resources: 8 GPUs Modality: RGB Name: tsm_k400_pretrained_r50_1x1x8_25e_ucf101_rgb Results: - Dataset: UCF101 Metrics: Top 1 Accuracy: 94.5 Top 5 Accuracy: 99.58 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_k400_pretrained_r50_1x1x8_25e_ucf101_rgb/20210605_182720.log.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_k400_pretrained_r50_1x1x8_25e_ucf101_rgb/20210605_182720.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_k400_pretrained_r50_1x1x8_25e_ucf101_rgb/tsm_k400_pretrained_r50_1x1x8_25e_ucf101_rgb_20210630-1fae312b.pth gpu_mem(M): '10389' - Config: configs/recognition/tsm/tsm_k400_pretrained_r50_1x1x16_25e_ucf101_rgb.py In Collection: TSM Metadata: Architecture: ResNet50 Batch Size: 6 Epochs: 25 FLOPs: 65921327104 Parameters: 23714981 Pretrained: Kinetics400 Training Data: UCF101 Training Resources: 8 GPUs Modality: RGB Name: tsm_k400_pretrained_r50_1x1x16_25e_ucf101_rgb Results: - Dataset: UCF101 Metrics: Top 1 Accuracy: 94.58 Top 5 Accuracy: 99.37 Task: Action Recognition Training Json Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_k400_pretrained_r50_1x1x16_25e_ucf101_rgb/20210605_182720.log.json Training Log: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_k400_pretrained_r50_1x1x16_25e_ucf101_rgb/20210605_182720.log Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_k400_pretrained_r50_1x1x16_25e_ucf101_rgb/tsm_k400_pretrained_r50_1x1x16_25e_ucf101_rgb_20210630-8df9c358.pth gpu_mem(M): '10389' - Config: configs/recognition/tsm/tsm_mobilenetv2_dense_1x1x8_100e_kinetics400_rgb.py In Collection: TSM Metadata: Architecture: MobileNetV2 Batch Size: 8 Epochs: 100 FLOPs: 3337519104 Parameters: 2736272 Pretrained: ImageNet Resolution: short-side 320 Training Data: Kinetics-400 Training Resources: 8 GPUs Modality: RGB Name: tsm_mobilenetv2_dense_1x1x8_kinetics400_rgb_port Results: - Dataset: Kinetics-400 Metrics: Top 1 Accuracy: 69.89 Top 5 Accuracy: 89.01 Task: Action Recognition Weights: https://download.openmmlab.com/mmaction/recognition/tsm/tsm_mobilenetv2_dense_1x1x8_kinetics400_rgb_port_20210922-aa5cadf6.pth gpu_mem(M): '3385'