Reviews: Arbicon-Net: Arbitrary Continuous Geometric Transformation Networks for Image Registration

The paper presents a neural network model for image registration, which generates an arbitrary displacement field to transform the input image in a way that matches the target. This neural network has several components, including a common feature extraction model that results in a 4D tensor with the correlations of local features from both images. The tensor is then transformed into a vector representation of the transformation, and later used to reconstruct a displacement field. COMMENTS Overall, the work is relatively well presented and provides details to understand most of the formulation and solution. However, there are some confusing aspects that could be clarified or stated more prominently.