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ResNet-2Plus1D

Video Classification
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android
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ResNet-2Plus1D
File size: 12,572 Bytes
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---
library_name: pytorch
license: other
tags:
- backbone
- android
pipeline_tag: video-classification

---

![](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnet_2plus1d/web-assets/model_demo.png)

# ResNet-2Plus1D: Optimized for Qualcomm Devices

ResNet (2+1)D Convolutions is a network which explicitly factorizes 3D convolution into two separate and successive operations, a 2D spatial convolution and a 1D temporal convolution. It used for video understanding applications.

This is based on the implementation of ResNet-2Plus1D found [here](https://github.com/pytorch/vision/blob/main/torchvision/models/video/resnet.py).
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/src/qai_hub_models/models/resnet_2plus1d) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary).

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.

## Getting Started
There are two ways to deploy this model on your device:

### Option 1: Download Pre-Exported Models

Below are pre-exported model assets ready for deployment.

| Runtime | Precision | Chipset | SDK Versions | Download |
|---|---|---|---|---|
| ONNX | float | Universal | QAIRT 2.42, ONNX Runtime 1.24.3 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnet_2plus1d/releases/v0.53.1/resnet_2plus1d-onnx-float.zip)
| ONNX | w8a8 | Universal | QAIRT 2.42, ONNX Runtime 1.24.3 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnet_2plus1d/releases/v0.53.1/resnet_2plus1d-onnx-w8a8.zip)
| QNN_DLC | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnet_2plus1d/releases/v0.53.1/resnet_2plus1d-qnn_dlc-float.zip)
| QNN_DLC | w8a8 | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnet_2plus1d/releases/v0.53.1/resnet_2plus1d-qnn_dlc-w8a8.zip)
| TFLITE | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnet_2plus1d/releases/v0.53.1/resnet_2plus1d-tflite-float.zip)
| TFLITE | w8a8 | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnet_2plus1d/releases/v0.53.1/resnet_2plus1d-tflite-w8a8.zip)

For more device-specific assets and performance metrics, visit **[ResNet-2Plus1D on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/resnet_2plus1d)**.


### Option 2: Export with Custom Configurations

Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/main/src/qai_hub_models/models/resnet_2plus1d) Python library to compile and export the model with your own:
- Custom weights (e.g., fine-tuned checkpoints)
- Custom input shapes
- Target device and runtime configurations

This option is ideal if you need to customize the model beyond the default configuration provided here.

See our repository for [ResNet-2Plus1D on GitHub](https://github.com/qualcomm/ai-hub-models/blob/main/src/qai_hub_models/models/resnet_2plus1d) for usage instructions.

## Model Details

**Model Type:** Model_use_case.video_classification

**Model Stats:**
- Model checkpoint: Kinetics-400
- Input resolution: 112x112
- Number of parameters: 31.5M
- Model size (float): 120 MB
- Model size (w8a8): 30.8 MB

## Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
|---|---|---|---|---|---|---
| ResNet-2Plus1D | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 5.523 ms | 2 - 214 MB | NPU
| ResNet-2Plus1D | ONNX | float | Snapdragon® 8 Elite Mobile | 7.215 ms | 0 - 209 MB | NPU
| ResNet-2Plus1D | ONNX | float | Snapdragon® X2 Elite | 6.145 ms | 60 - 60 MB | NPU
| ResNet-2Plus1D | ONNX | float | Snapdragon® X Elite | 12.211 ms | 60 - 60 MB | NPU
| ResNet-2Plus1D | ONNX | float | Snapdragon® X Elite | 12.211 ms | 60 - 60 MB | NPU
| ResNet-2Plus1D | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 9.079 ms | 2 - 299 MB | NPU
| ResNet-2Plus1D | ONNX | float | Qualcomm® QCS8550 (Proxy) | 12.028 ms | 2 - 5 MB | NPU
| ResNet-2Plus1D | ONNX | float | Qualcomm® QCS9075 | 21.357 ms | 2 - 7 MB | NPU
| ResNet-2Plus1D | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 7.215 ms | 0 - 209 MB | NPU
| ResNet-2Plus1D | ONNX | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 1.923 ms | 0 - 191 MB | NPU
| ResNet-2Plus1D | ONNX | w8a8 | Snapdragon® 8 Elite Mobile | 2.628 ms | 0 - 189 MB | NPU
| ResNet-2Plus1D | ONNX | w8a8 | Snapdragon® X2 Elite | 2.039 ms | 31 - 31 MB | NPU
| ResNet-2Plus1D | ONNX | w8a8 | Snapdragon® X Elite | 4.546 ms | 31 - 31 MB | NPU
| ResNet-2Plus1D | ONNX | w8a8 | Snapdragon® X Elite | 4.546 ms | 31 - 31 MB | NPU
| ResNet-2Plus1D | ONNX | w8a8 | Snapdragon® 8 Gen 3 Mobile | 3.267 ms | 0 - 224 MB | NPU
| ResNet-2Plus1D | ONNX | w8a8 | Qualcomm® QCS6490 | 317.614 ms | 97 - 127 MB | CPU
| ResNet-2Plus1D | ONNX | w8a8 | Qualcomm® QCS8550 (Proxy) | 4.274 ms | 0 - 227 MB | NPU
| ResNet-2Plus1D | ONNX | w8a8 | Qualcomm® QCS9075 | 4.11 ms | 1 - 3 MB | NPU
| ResNet-2Plus1D | ONNX | w8a8 | Qualcomm® QCM6690 | 301.447 ms | 100 - 108 MB | CPU
| ResNet-2Plus1D | ONNX | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 2.628 ms | 0 - 189 MB | NPU
| ResNet-2Plus1D | ONNX | w8a8 | Snapdragon® 7 Gen 4 Mobile | 269.891 ms | 67 - 75 MB | CPU
| ResNet-2Plus1D | ONNX | w8a8 | Snapdragon® 7 Gen 4 Mobile | 269.891 ms | 67 - 75 MB | CPU
| ResNet-2Plus1D | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 5.641 ms | 2 - 227 MB | NPU
| ResNet-2Plus1D | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 7.17 ms | 0 - 217 MB | NPU
| ResNet-2Plus1D | QNN_DLC | float | Snapdragon® X2 Elite | 6.646 ms | 2 - 2 MB | NPU
| ResNet-2Plus1D | QNN_DLC | float | Snapdragon® X Elite | 12.87 ms | 2 - 2 MB | NPU
| ResNet-2Plus1D | QNN_DLC | float | Snapdragon® X Elite | 12.87 ms | 2 - 2 MB | NPU
| ResNet-2Plus1D | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 9.25 ms | 0 - 291 MB | NPU
| ResNet-2Plus1D | QNN_DLC | float | Qualcomm® QCS8275 (Proxy) | 81.878 ms | 2 - 215 MB | NPU
| ResNet-2Plus1D | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 12.631 ms | 2 - 4 MB | NPU
| ResNet-2Plus1D | QNN_DLC | float | Qualcomm® SA8775P | 21.262 ms | 1 - 215 MB | NPU
| ResNet-2Plus1D | QNN_DLC | float | Qualcomm® SA8775P | 21.262 ms | 1 - 215 MB | NPU
| ResNet-2Plus1D | QNN_DLC | float | Qualcomm® SA8775P | 21.262 ms | 1 - 215 MB | NPU
| ResNet-2Plus1D | QNN_DLC | float | Qualcomm® QCS9075 | 23.466 ms | 2 - 6 MB | NPU
| ResNet-2Plus1D | QNN_DLC | float | Qualcomm® QCS8450 (Proxy) | 29.007 ms | 0 - 268 MB | NPU
| ResNet-2Plus1D | QNN_DLC | float | Qualcomm® SA7255P | 81.878 ms | 2 - 215 MB | NPU
| ResNet-2Plus1D | QNN_DLC | float | Qualcomm® SA8295P | 22.738 ms | 0 - 197 MB | NPU
| ResNet-2Plus1D | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 7.17 ms | 0 - 217 MB | NPU
| ResNet-2Plus1D | QNN_DLC | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 1.849 ms | 0 - 184 MB | NPU
| ResNet-2Plus1D | QNN_DLC | w8a8 | Snapdragon® 8 Elite Mobile | 2.565 ms | 0 - 182 MB | NPU
| ResNet-2Plus1D | QNN_DLC | w8a8 | Snapdragon® X2 Elite | 2.366 ms | 1 - 1 MB | NPU
| ResNet-2Plus1D | QNN_DLC | w8a8 | Snapdragon® X Elite | 4.906 ms | 1 - 1 MB | NPU
| ResNet-2Plus1D | QNN_DLC | w8a8 | Snapdragon® X Elite | 4.906 ms | 1 - 1 MB | NPU
| ResNet-2Plus1D | QNN_DLC | w8a8 | Snapdragon® 8 Gen 3 Mobile | 3.339 ms | 1 - 219 MB | NPU
| ResNet-2Plus1D | QNN_DLC | w8a8 | Qualcomm® QCS6490 | 19.672 ms | 3 - 5 MB | NPU
| ResNet-2Plus1D | QNN_DLC | w8a8 | Qualcomm® QCS8275 (Proxy) | 13.385 ms | 1 - 183 MB | NPU
| ResNet-2Plus1D | QNN_DLC | w8a8 | Qualcomm® QCS8550 (Proxy) | 4.599 ms | 1 - 3 MB | NPU
| ResNet-2Plus1D | QNN_DLC | w8a8 | Qualcomm® SA8775P | 4.698 ms | 1 - 187 MB | NPU
| ResNet-2Plus1D | QNN_DLC | w8a8 | Qualcomm® SA8775P | 4.698 ms | 1 - 187 MB | NPU
| ResNet-2Plus1D | QNN_DLC | w8a8 | Qualcomm® SA8775P | 4.698 ms | 1 - 187 MB | NPU
| ResNet-2Plus1D | QNN_DLC | w8a8 | Qualcomm® QCS9075 | 4.76 ms | 1 - 3 MB | NPU
| ResNet-2Plus1D | QNN_DLC | w8a8 | Qualcomm® QCM6690 | 82.143 ms | 1 - 198 MB | NPU
| ResNet-2Plus1D | QNN_DLC | w8a8 | Qualcomm® QCS8450 (Proxy) | 7.861 ms | 1 - 217 MB | NPU
| ResNet-2Plus1D | QNN_DLC | w8a8 | Qualcomm® SA7255P | 13.385 ms | 1 - 183 MB | NPU
| ResNet-2Plus1D | QNN_DLC | w8a8 | Qualcomm® SA8295P | 7.843 ms | 0 - 180 MB | NPU
| ResNet-2Plus1D | QNN_DLC | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 2.565 ms | 0 - 182 MB | NPU
| ResNet-2Plus1D | QNN_DLC | w8a8 | Snapdragon® 7 Gen 4 Mobile | 7.895 ms | 1 - 189 MB | NPU
| ResNet-2Plus1D | QNN_DLC | w8a8 | Snapdragon® 7 Gen 4 Mobile | 7.895 ms | 1 - 189 MB | NPU
| ResNet-2Plus1D | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 257.361 ms | 0 - 247 MB | NPU
| ResNet-2Plus1D | TFLITE | float | Snapdragon® 8 Elite Mobile | 256.547 ms | 0 - 242 MB | NPU
| ResNet-2Plus1D | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 294.591 ms | 0 - 305 MB | NPU
| ResNet-2Plus1D | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 714.781 ms | 0 - 237 MB | NPU
| ResNet-2Plus1D | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 374.47 ms | 0 - 2 MB | NPU
| ResNet-2Plus1D | TFLITE | float | Qualcomm® SA8775P | 392.912 ms | 0 - 235 MB | NPU
| ResNet-2Plus1D | TFLITE | float | Qualcomm® SA8775P | 392.912 ms | 0 - 235 MB | NPU
| ResNet-2Plus1D | TFLITE | float | Qualcomm® SA8775P | 392.912 ms | 0 - 235 MB | NPU
| ResNet-2Plus1D | TFLITE | float | Qualcomm® QCS9075 | 390.284 ms | 0 - 66 MB | NPU
| ResNet-2Plus1D | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 429.829 ms | 0 - 301 MB | NPU
| ResNet-2Plus1D | TFLITE | float | Qualcomm® SA7255P | 714.781 ms | 0 - 237 MB | NPU
| ResNet-2Plus1D | TFLITE | float | Qualcomm® SA8295P | 453.705 ms | 0 - 228 MB | NPU
| ResNet-2Plus1D | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 256.547 ms | 0 - 242 MB | NPU
| ResNet-2Plus1D | TFLITE | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 643.395 ms | 0 - 454 MB | NPU
| ResNet-2Plus1D | TFLITE | w8a8 | Snapdragon® 8 Elite Mobile | 507.9 ms | 0 - 546 MB | NPU
| ResNet-2Plus1D | TFLITE | w8a8 | Snapdragon® 8 Gen 3 Mobile | 586.817 ms | 0 - 516 MB | NPU
| ResNet-2Plus1D | TFLITE | w8a8 | Qualcomm® QCS6490 | 1781.787 ms | 267 - 428 MB | NPU
| ResNet-2Plus1D | TFLITE | w8a8 | Qualcomm® QCS8275 (Proxy) | 1517.615 ms | 0 - 438 MB | NPU
| ResNet-2Plus1D | TFLITE | w8a8 | Qualcomm® QCS8550 (Proxy) | 751.095 ms | 0 - 3 MB | NPU
| ResNet-2Plus1D | TFLITE | w8a8 | Qualcomm® SA8775P | 799.258 ms | 0 - 440 MB | NPU
| ResNet-2Plus1D | TFLITE | w8a8 | Qualcomm® SA8775P | 799.258 ms | 0 - 440 MB | NPU
| ResNet-2Plus1D | TFLITE | w8a8 | Qualcomm® SA8775P | 799.258 ms | 0 - 440 MB | NPU
| ResNet-2Plus1D | TFLITE | w8a8 | Qualcomm® QCS9075 | 573.098 ms | 0 - 65 MB | NPU
| ResNet-2Plus1D | TFLITE | w8a8 | Qualcomm® QCM6690 | 1602.624 ms | 296 - 458 MB | NPU
| ResNet-2Plus1D | TFLITE | w8a8 | Qualcomm® QCS8450 (Proxy) | 866.104 ms | 0 - 463 MB | NPU
| ResNet-2Plus1D | TFLITE | w8a8 | Qualcomm® SA7255P | 1517.615 ms | 0 - 438 MB | NPU
| ResNet-2Plus1D | TFLITE | w8a8 | Qualcomm® SA8295P | 871.702 ms | 0 - 435 MB | NPU
| ResNet-2Plus1D | TFLITE | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 507.9 ms | 0 - 546 MB | NPU
| ResNet-2Plus1D | TFLITE | w8a8 | Snapdragon® 7 Gen 4 Mobile | 1215.928 ms | 295 - 365 MB | NPU
| ResNet-2Plus1D | TFLITE | w8a8 | Snapdragon® 7 Gen 4 Mobile | 1215.928 ms | 295 - 365 MB | NPU

## License
* The license for the original implementation of ResNet-2Plus1D can be found
  [here](https://github.com/pytorch/vision/blob/main/LICENSE).

## References
* [A Closer Look at Spatiotemporal Convolutions for Action Recognition](https://arxiv.org/abs/1711.11248)
* [Source Model Implementation](https://github.com/pytorch/vision/blob/main/torchvision/models/video/resnet.py)

## Community
* Join [our AI Hub Slack community](https://aihub.qualcomm.com/community/slack) to collaborate, post questions and learn more about on-device AI.
* For questions or feedback please [reach out to us](mailto:ai-hub-support@qti.qualcomm.com).