OptiDepth

OptiDepth is an advanced joint model designed to overcome challenges in real-time depth estimation, particularly on reflective surfaces like glass and mirrors. Leveraging Quantization-Aware Training (QAT) and Post-Training Quantization (PTQ), it optimizes models such as MirrorNet and GDNet, reducing memory usage by 62% and 70%, respectively, while improving computational efficiency. This enables faster inference on edge devices like the OAK-D camera, making it ideal for applications requiring real-time depth perception in complex environments.