Real-time Aleatoric Uncertainty Estimation in Semantic Segmentation
Added real-time aleatoric uncertainty estimation to a semantic segmentation pipeline so uncertain regions can be filtered before downstream use.
Approach
- Added a ConfidNet FCN uncertainty branch to the existing DDRNet segmentation network.
- Trained the model to estimate segmentation uncertainty alongside class predictions.
- Used thresholding to filter uncertain segmented areas in real time.
