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Video-MAE

Video Classification
PyTorch
backbone
android
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v0.48.0

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See https://github.com/qualcomm/ai-hub-models/releases/v0.48.0 for changelog.

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  1. README.md +46 -36
README.md CHANGED
@@ -15,7 +15,7 @@ pipeline_tag: video-classification
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  Video MAE (Masked Auto Encoder) is a network for doing video classification that uses the ViT (Vision Transformer) backbone.
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  This is based on the implementation of Video-MAE found [here](https://github.com/MCG-NJU/VideoMAE).
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- This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the [Qualcomm® AI Hub Models](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/video_mae) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary).
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  Qualcomm AI Hub Models uses [Qualcomm AI Hub Workbench](https://workbench.aihub.qualcomm.com) to compile, profile, and evaluate this model. [Sign up](https://myaccount.qualcomm.com/signup) to run these models on a hosted Qualcomm® device.
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@@ -28,25 +28,25 @@ Below are pre-exported model assets ready for deployment.
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  | Runtime | Precision | Chipset | SDK Versions | Download |
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  |---|---|---|---|---|
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- | ONNX | float | Universal | QAIRT 2.42, ONNX Runtime 1.24.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/video_mae/releases/v0.47.0/video_mae-onnx-float.zip)
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- | ONNX | w8a16 | Universal | QAIRT 2.42, ONNX Runtime 1.24.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/video_mae/releases/v0.47.0/video_mae-onnx-w8a16.zip)
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- | QNN_DLC | float | Universal | QAIRT 2.43 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/video_mae/releases/v0.47.0/video_mae-qnn_dlc-float.zip)
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- | QNN_DLC | w8a16 | Universal | QAIRT 2.43 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/video_mae/releases/v0.47.0/video_mae-qnn_dlc-w8a16.zip)
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- | TFLITE | float | Universal | QAIRT 2.43, TFLite 2.17.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/video_mae/releases/v0.47.0/video_mae-tflite-float.zip)
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  For more device-specific assets and performance metrics, visit **[Video-MAE on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/video_mae)**.
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39
 
40
  ### Option 2: Export with Custom Configurations
41
 
42
- Use the [Qualcomm® AI Hub Models](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/video_mae) Python library to compile and export the model with your own:
43
  - Custom weights (e.g., fine-tuned checkpoints)
44
  - Custom input shapes
45
  - Target device and runtime configurations
46
 
47
  This option is ideal if you need to customize the model beyond the default configuration provided here.
48
 
49
- See our repository for [Video-MAE on GitHub](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/video_mae) for usage instructions.
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51
  ## Model Details
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@@ -61,34 +61,44 @@ See our repository for [Video-MAE on GitHub](https://github.com/quic/ai-hub-mode
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  ## Performance Summary
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  | Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
63
  |---|---|---|---|---|---|---
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- | Video-MAE | ONNX | float | Snapdragon® X Elite | 587.026 ms | 187 - 187 MB | NPU
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- | Video-MAE | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 368.95 ms | 2 - 1260 MB | NPU
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- | Video-MAE | ONNX | float | Qualcomm® QCS8550 (Proxy) | 568.266 ms | 0 - 5 MB | NPU
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- | Video-MAE | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 390.549 ms | 2 - 1045 MB | NPU
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- | Video-MAE | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 459.094 ms | 9 - 1089 MB | NPU
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- | Video-MAE | ONNX | float | Snapdragon® X2 Elite | 448.083 ms | 187 - 187 MB | NPU
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- | Video-MAE | QNN_DLC | float | Snapdragon® X Elite | 472.261 ms | 9 - 9 MB | NPU
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- | Video-MAE | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 381.871 ms | 9 - 1170 MB | NPU
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- | Video-MAE | QNN_DLC | float | Qualcomm® QCS8275 (Proxy) | 1091.288 ms | 1 - 948 MB | NPU
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- | Video-MAE | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 453.084 ms | 9 - 12 MB | NPU
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- | Video-MAE | QNN_DLC | float | Qualcomm® SA8775P | 497.143 ms | 0 - 972 MB | NPU
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- | Video-MAE | QNN_DLC | float | Qualcomm® QCS9075 | 514.195 ms | 9 - 20 MB | NPU
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- | Video-MAE | QNN_DLC | float | Qualcomm® QCS8450 (Proxy) | 580.221 ms | 9 - 1067 MB | NPU
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- | Video-MAE | QNN_DLC | float | Qualcomm® SA7255P | 1091.288 ms | 1 - 948 MB | NPU
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- | Video-MAE | QNN_DLC | float | Qualcomm® SA8295P | 569.0 ms | 0 - 858 MB | NPU
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- | Video-MAE | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 260.228 ms | 9 - 969 MB | NPU
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- | Video-MAE | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 329.664 ms | 9 - 962 MB | NPU
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- | Video-MAE | QNN_DLC | float | Snapdragon® X2 Elite | 295.799 ms | 9 - 9 MB | NPU
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- | Video-MAE | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 101.855 ms | 0 - 1168 MB | NPU
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- | Video-MAE | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 5585.078 ms | 42 - 59 MB | CPU
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- | Video-MAE | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 140.998 ms | 0 - 4 MB | NPU
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- | Video-MAE | TFLITE | float | Qualcomm® SA8775P | 161.076 ms | 0 - 955 MB | NPU
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- | Video-MAE | TFLITE | float | Qualcomm® QCS9075 | 172.2 ms | 0 - 207 MB | NPU
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- | Video-MAE | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 296.47 ms | 1 - 1113 MB | NPU
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- | Video-MAE | TFLITE | float | Qualcomm® SA7255P | 5585.078 ms | 42 - 59 MB | CPU
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- | Video-MAE | TFLITE | float | Qualcomm® SA8295P | 214.768 ms | 0 - 907 MB | NPU
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- | Video-MAE | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 74.046 ms | 0 - 965 MB | NPU
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- | Video-MAE | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 60.611 ms | 0 - 965 MB | NPU
 
 
 
 
 
 
 
 
 
 
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93
  ## License
94
  * The license for the original implementation of Video-MAE can be found
 
15
  Video MAE (Masked Auto Encoder) is a network for doing video classification that uses the ViT (Vision Transformer) backbone.
16
 
17
  This is based on the implementation of Video-MAE found [here](https://github.com/MCG-NJU/VideoMAE).
18
+ This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/main/qai_hub_models/models/video_mae) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary).
19
 
20
  Qualcomm AI Hub Models uses [Qualcomm AI Hub Workbench](https://workbench.aihub.qualcomm.com) to compile, profile, and evaluate this model. [Sign up](https://myaccount.qualcomm.com/signup) to run these models on a hosted Qualcomm® device.
21
 
 
28
 
29
  | Runtime | Precision | Chipset | SDK Versions | Download |
30
  |---|---|---|---|---|
31
+ | ONNX | float | Universal | QAIRT 2.42, ONNX Runtime 1.24.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/video_mae/releases/v0.48.0/video_mae-onnx-float.zip)
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+ | ONNX | w8a16 | Universal | QAIRT 2.42, ONNX Runtime 1.24.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/video_mae/releases/v0.48.0/video_mae-onnx-w8a16.zip)
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+ | QNN_DLC | float | Universal | QAIRT 2.43 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/video_mae/releases/v0.48.0/video_mae-qnn_dlc-float.zip)
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+ | QNN_DLC | w8a16 | Universal | QAIRT 2.43 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/video_mae/releases/v0.48.0/video_mae-qnn_dlc-w8a16.zip)
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+ | TFLITE | float | Universal | QAIRT 2.43, TFLite 2.17.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/video_mae/releases/v0.48.0/video_mae-tflite-float.zip)
36
 
37
  For more device-specific assets and performance metrics, visit **[Video-MAE on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/video_mae)**.
38
 
39
 
40
  ### Option 2: Export with Custom Configurations
41
 
42
+ Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/main/qai_hub_models/models/video_mae) Python library to compile and export the model with your own:
43
  - Custom weights (e.g., fine-tuned checkpoints)
44
  - Custom input shapes
45
  - Target device and runtime configurations
46
 
47
  This option is ideal if you need to customize the model beyond the default configuration provided here.
48
 
49
+ See our repository for [Video-MAE on GitHub](https://github.com/qualcomm/ai-hub-models/blob/main/qai_hub_models/models/video_mae) for usage instructions.
50
 
51
  ## Model Details
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  ## Performance Summary
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  | Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
63
  |---|---|---|---|---|---|---
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+ | Video-MAE | ONNX | float | Snapdragon® X2 Elite | 465.083 ms | 188 - 188 MB | NPU
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+ | Video-MAE | ONNX | float | Snapdragon® X Elite | 668.776 ms | 188 - 188 MB | NPU
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+ | Video-MAE | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 388.833 ms | 9 - 1257 MB | NPU
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+ | Video-MAE | ONNX | float | Qualcomm® QCS8550 (Proxy) | 644.907 ms | 0 - 219 MB | NPU
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+ | Video-MAE | ONNX | float | Qualcomm® QCS9075 | 686.387 ms | 9 - 21 MB | NPU
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+ | Video-MAE | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 394.489 ms | 0 - 979 MB | NPU
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+ | Video-MAE | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 444.692 ms | 9 - 1065 MB | NPU
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+ | Video-MAE | ONNX | w8a16 | Snapdragon® X2 Elite | 323.006 ms | 123 - 123 MB | NPU
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+ | Video-MAE | ONNX | w8a16 | Snapdragon® X Elite | 489.095 ms | 129 - 129 MB | NPU
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+ | Video-MAE | ONNX | w8a16 | Snapdragon® 8 Gen 3 Mobile | 447.917 ms | 5 - 1858 MB | NPU
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+ | Video-MAE | ONNX | w8a16 | Qualcomm® QCS6490 | 9057.031 ms | 363 - 381 MB | CPU
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+ | Video-MAE | ONNX | w8a16 | Qualcomm® QCS8550 (Proxy) | 473.026 ms | 0 - 160 MB | NPU
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+ | Video-MAE | ONNX | w8a16 | Qualcomm® QCM6690 | 4452.468 ms | 326 - 338 MB | CPU
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+ | Video-MAE | ONNX | w8a16 | Snapdragon® 8 Elite For Galaxy Mobile | 278.713 ms | 0 - 1538 MB | NPU
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+ | Video-MAE | ONNX | w8a16 | Snapdragon® 7 Gen 4 Mobile | 4377.307 ms | 376 - 388 MB | CPU
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+ | Video-MAE | ONNX | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 323.42 ms | 5 - 1549 MB | NPU
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+ | Video-MAE | QNN_DLC | float | Snapdragon® X2 Elite | 249.277 ms | 9 - 9 MB | NPU
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+ | Video-MAE | QNN_DLC | float | Snapdragon® X Elite | 1308.348 ms | 9 - 9 MB | NPU
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+ | Video-MAE | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 414.95 ms | 9 - 1110 MB | NPU
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+ | Video-MAE | QNN_DLC | float | Qualcomm® QCS8275 (Proxy) | 2499.681 ms | 1 - 889 MB | NPU
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+ | Video-MAE | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 1249.753 ms | 9 - 12 MB | NPU
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+ | Video-MAE | QNN_DLC | float | Qualcomm® SA8775P | 6237.053 ms | 1 - 889 MB | NPU
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+ | Video-MAE | QNN_DLC | float | Qualcomm® QCS9075 | 519.754 ms | 9 - 20 MB | NPU
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+ | Video-MAE | QNN_DLC | float | Qualcomm® QCS8450 (Proxy) | 585.147 ms | 9 - 1025 MB | NPU
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+ | Video-MAE | QNN_DLC | float | Qualcomm® SA7255P | 2499.681 ms | 1 - 889 MB | NPU
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+ | Video-MAE | QNN_DLC | float | Qualcomm® SA8295P | 655.834 ms | 0 - 843 MB | NPU
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+ | Video-MAE | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 307.435 ms | 9 - 934 MB | NPU
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+ | Video-MAE | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 322.365 ms | 9 - 943 MB | NPU
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+ | Video-MAE | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 103.807 ms | 0 - 1114 MB | NPU
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+ | Video-MAE | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 428.414 ms | 0 - 918 MB | NPU
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+ | Video-MAE | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 141.755 ms | 0 - 3 MB | NPU
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+ | Video-MAE | TFLITE | float | Qualcomm® SA8775P | 164.5 ms | 0 - 921 MB | NPU
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+ | Video-MAE | TFLITE | float | Qualcomm® QCS9075 | 176.822 ms | 0 - 207 MB | NPU
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+ | Video-MAE | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 302.041 ms | 0 - 1056 MB | NPU
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+ | Video-MAE | TFLITE | float | Qualcomm® SA7255P | 428.414 ms | 0 - 918 MB | NPU
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+ | Video-MAE | TFLITE | float | Qualcomm® SA8295P | 216.681 ms | 0 - 872 MB | NPU
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+ | Video-MAE | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 81.01 ms | 0 - 923 MB | NPU
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+ | Video-MAE | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 63.809 ms | 0 - 941 MB | NPU
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103
  ## License
104
  * The license for the original implementation of Video-MAE can be found