  The advance of image editing techniques allows users to create artistic
works, but the manipulated regions may be incompatible with the background.
Localizing the inharmonious region is an appealing yet challenging task.
Realizing that this task requires effective aggregation of multi-scale
contextual information and suppression of redundant information, we design
novel Bi-directional Feature Integration (BFI) block and Global-context Guided
Decoder (GGD) block to fuse multi-scale features in the encoder and decoder
respectively. We also employ Mask-guided Dual Attention (MDA) block between the
encoder and decoder to suppress the redundant information. Experiments on the
image harmonization dataset demonstrate that our method achieves competitive
performance for inharmonious region localization. The source code is available
at https://github.com/bcmi/DIRL.
