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--- |
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license: other |
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license_name: aplux-model-farm-license |
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license_link: https://aiot.aidlux.com/api/v1/files/license/model_farm_license_en.pdf |
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pipeline_tag: object-detection |
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tags: |
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- AIoT |
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- QNN |
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--- |
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.png&w=640&q=75) |
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## Facial-Landmark-Detection: Pose Estimation |
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Facial-Landmark-Detection is a lightweight deep learning model for real-time facial keypoint detection (e.g., eyes, nose tip, mouth corners), optimized via multi-task learning and attention mechanisms for robustness in complex scenarios. It employs a hybrid backbone (e.g., MobileNetV3-HRNet) with dynamic coordinate regression to handle occlusion, lighting variations, and extreme poses, supporting 68/106-point high-precision localization. Through knowledge distillation, the model is compressed below 1MB parameters, achieving NRMSE <4.5% on 300W and WFLW datasets with 30+ FPS on mobile devices—10x faster than traditional Dlib. Ideal for AR virtual makeup, expression analysis, face alignment, and medical facial assessment, it balances edge deployment efficiency and sub-millimeter accuracy, with INT8 quantization for ultra-low latency. |
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### Source model |
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- Input shape: 1x3x128x128 |
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- Number of parameters: 5.17M |
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- Model size: 20.95M |
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- Output shape: 1x265 |
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The source model can be found [here](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/facemap_3dmm/model.py) |
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## Performance Reference |
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Please search model by model name in [Model Farm](https://aiot.aidlux.com/en/models) |
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## Inference & Model Conversion |
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Please search model by model name in [Model Farm](https://aiot.aidlux.com/en/models) |
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## License |
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- Source Model: [BSD-3-CLAUSE](https://github.com/quic/ai-hub-models/blob/main/LICENSE) |
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- Deployable Model: [APLUX-MODEL-FARM-LICENSE](https://aiot.aidlux.com/api/v1/files/license/model_farm_license_en.pdf) |
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