Semantic Change Detection with Asymmetric Siamese Networks

Understand

Given two multi-temporal aerial images, semantic change detection aims to locate the land-cover variations and identify their change types with pixel-wise boundaries.

• This problem is vital in many earth vision related tasks, such as precise urban planning and natural resource management.
• Existing state-of-the-art algorithms mainly identify the changed pixels by applying homogeneous operations on each input image and comparing the extracted features.
• However, in changed regions, totally different land-cover distributions often require heterogeneous features extraction procedures w.r.t each input.