library_name: pytorch
license: other
tags:
- android
pipeline_tag: depth-estimation
CREStereo: Optimized for Qualcomm Devices
CREStereo (Cascaded Recurrent Network with Adaptive Correlation) is a CVPR 2022 Oral paper that achieves state-of-the-art stereo matching accuracy.
This is based on the implementation of CREStereo 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 2.45, ONNX Runtime 1.27.1 | Download |
| QNN_DLC | float | Universal | QAIRT 2.45 | Download |
| TFLITE | float | Universal | QAIRT 2.45 | Download |
For more device-specific assets and performance metrics, visit CREStereo 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 CREStereo on GitHub for usage instructions.
Model Details
Model Type: Model_use_case.depth_estimation
Model Stats:
- Input: Rectified stereo pair — left and right RGB images
- Input resolution: 240x320
- Model checkpoint: CREStereo ETH3D pretrained (crestereo_eth3d.pt)
- Model size (float): 20.7 MB
- Number of parameters: 5.43M
- Output: Disparity map
Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit |
|---|---|---|---|---|---|---|
| CREStereo | ONNX | float | Snapdragon® X2 Elite | 87.564 ms | 2 - 2 MB | NPU |
| CREStereo | ONNX | float | Snapdragon® X Elite | 202.736 ms | 21 - 21 MB | NPU |
| CREStereo | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 144.369 ms | 3 - 1334 MB | NPU |
| CREStereo | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 328.168 ms | 3 - 1366 MB | NPU |
| CREStereo | ONNX | float | Qualcomm® Dragonwing™ IQ-8275 | 271.157 ms | 2 - 6 MB | NPU |
| CREStereo | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 200.076 ms | 0 - 25 MB | NPU |
| CREStereo | ONNX | float | Qualcomm® QCS8450 | 328.168 ms | 3 - 1366 MB | NPU |
| CREStereo | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 269.024 ms | 2 - 5 MB | NPU |
| CREStereo | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 202.736 ms | 21 - 21 MB | NPU |
| CREStereo | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 111.31 ms | 1 - 1112 MB | NPU |
| CREStereo | ONNX | float | Snapdragon® 8 Elite Mobile | 111.31 ms | 1 - 1112 MB | NPU |
| CREStereo | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 79.199 ms | 1 - 837 MB | NPU |
| CREStereo | QNN_DLC | float | Snapdragon® X2 Elite | 88.18 ms | 2 - 2 MB | NPU |
| CREStereo | QNN_DLC | float | Snapdragon® X Elite | 203.778 ms | 2 - 2 MB | NPU |
| CREStereo | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 144.84 ms | 2 - 1242 MB | NPU |
| CREStereo | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 328.828 ms | 2 - 1292 MB | NPU |
| CREStereo | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-8275 | 271.144 ms | 2 - 7 MB | NPU |
| CREStereo | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-8275 | 797.535 ms | 3 - 1015 MB | NPU |
| CREStereo | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 199.896 ms | 3 - 6 MB | NPU |
| CREStereo | QNN_DLC | float | Qualcomm® SA8775P | 269.996 ms | 3 - 1059 MB | NPU |
| CREStereo | QNN_DLC | float | Qualcomm® SA8650P | 269.996 ms | 3 - 1059 MB | NPU |
| CREStereo | QNN_DLC | float | Qualcomm® SA8255P | 269.996 ms | 3 - 1059 MB | NPU |
| CREStereo | QNN_DLC | float | Qualcomm® QCS8450 | 328.828 ms | 2 - 1292 MB | NPU |
| CREStereo | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 269.305 ms | 4 - 8 MB | NPU |
| CREStereo | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 203.778 ms | 2 - 2 MB | NPU |
| CREStereo | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 111.55 ms | 3 - 1046 MB | NPU |
| CREStereo | QNN_DLC | float | Qualcomm® SA7255P | 797.535 ms | 3 - 1015 MB | NPU |
| CREStereo | QNN_DLC | float | Qualcomm® SA8295P | 312.046 ms | 3 - 1066 MB | NPU |
| CREStereo | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 111.55 ms | 3 - 1046 MB | NPU |
| CREStereo | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 79.208 ms | 1 - 748 MB | NPU |
| CREStereo | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 151.227 ms | 1 - 1672 MB | NPU |
| CREStereo | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 379.427 ms | 1 - 1643 MB | NPU |
| CREStereo | TFLITE | float | Qualcomm® Dragonwing™ IQ-8275 | 278.444 ms | 0 - 44 MB | NPU |
| CREStereo | TFLITE | float | Qualcomm® Dragonwing™ IQ-8275 | 809.84 ms | 1 - 1402 MB | NPU |
| CREStereo | TFLITE | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 216.12 ms | 0 - 7 MB | NPU |
| CREStereo | TFLITE | float | Qualcomm® SA8775P | 282.462 ms | 1 - 1411 MB | NPU |
| CREStereo | TFLITE | float | Qualcomm® SA8650P | 282.462 ms | 1 - 1411 MB | NPU |
| CREStereo | TFLITE | float | Qualcomm® SA8255P | 282.462 ms | 1 - 1411 MB | NPU |
| CREStereo | TFLITE | float | Qualcomm® QCS8450 | 379.427 ms | 1 - 1643 MB | NPU |
| CREStereo | TFLITE | float | Qualcomm® Dragonwing™ IQ-9075 | 281.541 ms | 0 - 43 MB | NPU |
| CREStereo | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 122.089 ms | 1 - 1377 MB | NPU |
| CREStereo | TFLITE | float | Qualcomm® SA7255P | 809.84 ms | 1 - 1402 MB | NPU |
| CREStereo | TFLITE | float | Qualcomm® SA8295P | 350.245 ms | 1 - 1383 MB | NPU |
| CREStereo | TFLITE | float | Snapdragon® 8 Elite Mobile | 122.089 ms | 1 - 1377 MB | NPU |
| CREStereo | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 88.324 ms | 0 - 1114 MB | NPU |
License
- The license for the original implementation of CREStereo can be found here.
References
- Practical Stereo Matching via Cascaded Recurrent Network with Adaptive Correlation
- 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.
