Shengxin Dai

A unified framework for failure and anomaly detection built on mask-level semantic segmentation

This work investigated intrinsic failures and anomalies in semantic segmentation and proposed a unified framework that manages these errors specifically for autonomous vehicles, and developed an anomaly fusion module that integrates data from both inlier and void masks, alongside pyramid features from the backbone, ult...