Dual Task Learning by Leveraging Both Dense Correspondence and Mis-Correspondence for Robust Change Detection With Imperfect Matches
Accurate change detection enables a wide range of tasks in visual surveillance, anomaly detection and mobile robotics. However, contemporary change detection approaches assume an ideal matching between the current and stored scenes, whereas only coarse matching is possible in real-world scenarios. T…