FQ-PETR: Fully Quantized Position Embedding Transformation for Multi-View 3D Object Detection

Understand

Camera-based multi-view 3D detection is crucial for autonomous driving.

• PETR and its variants (PETRs) excel in benchmarks but face deployment challenges due to high computational cost and memory footprint.
• Quantization is an effective technique for compressing deep neural networks by reducing the bit width of weights and activations.
• However, directly applying existing quantization methods to PETRs leads to severe accuracy degradation.