First-Order-Motion-Model: Optimized for Qualcomm Devices

FOMM is a machine learning model that animates a still image to mirror the movements from a target video.

This is based on the implementation of First-Order-Motion-Model found here. This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the Qualcomm® AI Hub Models library to export with custom configurations. More details on model performance across various devices, can be found here.

Qualcomm AI Hub Models uses Qualcomm AI Hub Workbench to compile, profile, and evaluate this model. Sign up 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 2.50, ONNX Runtime 1.30.0	Download

For more device-specific assets and performance metrics, visit First-Order-Motion-Model on Qualcomm® AI Hub.

Option 2: Export with Custom Configurations

Use the Qualcomm® AI Hub Models 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 First-Order-Motion-Model on GitHub for usage instructions.

Model Details

Model Type: Model_use_case.video_generation

Model Stats:

• Input resolution: 256x256
• Model checkpoint: vox-256
• Model size (detector) (float): 54.2 MB
• Model size (generator) (float): 174 MB

Performance Summary

Model	Runtime	Precision	Chipset	Inference Time (ms)	Peak Memory Range (MB)	Primary Compute Unit
detector	ONNX	float	Snapdragon® 8 Elite Gen 5 For Galaxy Mobile	2.786 ms	0 - 27 MB	NPU
detector	ONNX	float	Snapdragon® 8 Elite For Galaxy Mobile	2.936 ms	0 - 25 MB	NPU
detector	ONNX	float	Snapdragon® X2 Elite	2.712 ms	2 - 2 MB	NPU
detector	ONNX	float	Snapdragon® X Elite	4.642 ms	28 - 28 MB	NPU
detector	ONNX	float	Snapdragon® 8 Gen 3 Mobile	3.345 ms	0 - 36 MB	NPU
detector	ONNX	float	Snapdragon® 8 Gen 1 Mobile	7.386 ms	1 - 41 MB	NPU
detector	ONNX	float	Qualcomm® Dragonwing™ IQ-8275	6.703 ms	1 - 5 MB	NPU
detector	ONNX	float	Qualcomm® Dragonwing™ QCS8550 (Proxy)	4.53 ms	0 - 29 MB	NPU
detector	ONNX	float	Qualcomm® QCS8450	7.386 ms	1 - 41 MB	NPU
detector	ONNX	float	Qualcomm® Dragonwing™ IQ-9075	5.774 ms	1 - 4 MB	NPU
detector	ONNX	float	Qualcomm® Dragonwing™ IQ-X7181	4.642 ms	28 - 28 MB	NPU
detector	ONNX	float	Qualcomm® Dragonwing™ Q-8750	2.936 ms	0 - 25 MB	NPU
detector	TFLITE	float	Qualcomm® SA8650P	5.807 ms	0 - 29 MB	NPU
detector	TFLITE	float	Qualcomm® SA8255P	5.807 ms	0 - 29 MB	NPU
generator	ONNX	float	Snapdragon® 8 Elite Gen 5 For Galaxy Mobile	10.409 ms	14 - 181 MB	NPU
generator	ONNX	float	Snapdragon® 8 Elite For Galaxy Mobile	13.319 ms	13 - 169 MB	NPU
generator	ONNX	float	Snapdragon® X2 Elite	12.454 ms	23 - 23 MB	NPU
generator	ONNX	float	Snapdragon® X Elite	22.412 ms	89 - 89 MB	NPU
generator	ONNX	float	Snapdragon® 8 Gen 3 Mobile	15.907 ms	0 - 188 MB	NPU
generator	ONNX	float	Snapdragon® 8 Gen 1 Mobile	35.493 ms	17 - 200 MB	NPU
generator	ONNX	float	Qualcomm® Dragonwing™ IQ-8275	38.342 ms	16 - 21 MB	NPU
generator	ONNX	float	Qualcomm® Dragonwing™ QCS8550 (Proxy)	21.97 ms	18 - 21 MB	NPU
generator	ONNX	float	Qualcomm® QCS8450	35.493 ms	17 - 200 MB	NPU
generator	ONNX	float	Qualcomm® Dragonwing™ IQ-9075	32.995 ms	17 - 21 MB	NPU
generator	ONNX	float	Qualcomm® Dragonwing™ IQ-X7181	22.412 ms	89 - 89 MB	NPU
generator	ONNX	float	Qualcomm® Dragonwing™ Q-8750	13.319 ms	13 - 169 MB	NPU
generator	TFLITE	float	Qualcomm® SA8650P	545.416 ms	19 - 37 MB	CPU
generator	TFLITE	float	Qualcomm® SA8255P	545.416 ms	19 - 37 MB	CPU

License

• The license for the original implementation of First-Order-Motion-Model can be found here.

References

• First Order Motion Model for Image Animation
• Source Model Implementation

Community

• Join our AI Hub Slack community to collaborate, post questions and learn more about on-device AI.
• For questions or feedback please reach out to us.