This paper proposes a Recurrent Affine Transform Encoder (RATE) that can be used for image representation learning. We propose learning architecture enables CNN encoder to learn the affine transform parameter of images. The proposed decomposes an matrix into two matrices and learns them jointly in self-supervised manner. RATE is trained by unlabeled data without any ground truth infers input im...

Grid-based features have been proven to be as effective region-based in multi-modal tasks such visual question answering. However, its application image captioning encounters two main issues, namely, noisy and fragmented semantics. In this paper, we propose a novel feature selection scheme, with Relation-Aware Selection (RAS) Fine-grained Semantic Guidance (FSG) learning strategy. Based on the ...

‎Frames generalize orthonormal bases and allow representation of all the elements of the space‎. ‎Frames play significant role in signal and image processing‎, ‎which leads to many applications in informatics‎, ‎engineering‎, ‎medicine‎, ‎and probability‎. ‎In this paper‎, ‎we introduce the concepts of operator frame for the space $End_{mathcal{A}}^{ast}(mathcal{H})$ of all adjointable operator...