OrientedFormer: An End-to-End Transformer-Based Oriented Object Detector in Remote Sensing Images Publication date: IEEE Transactions on Geoscience and Remote Sensing 2024 Topic: Object detection Paper: https://arxiv.org/pdf/2409.19648v1.pdf GitHub: https://github.com/wokaikaixinxin/OrientedFormer Description: In this paper, we propose an end-to-end transformer-based oriented object detector, consisting of three dedicated modules to address these issues. First, Gaussian positional encoding is proposed to encode the angle, position, and size of oriented boxes using Gaussian distributions. Second, Wasserstein self-attention is proposed to introduce geometric relations and facilitate interaction between content and positional queries by utilizing Gaussian Wasserstein distance scores. Third, oriented cross-attention is proposed to align values and positional queries by rotating sampling points around the positional query according to their angles.