Oriented Object Detection with Transformer

• URL: http://arxiv.org/abs/2106.03146v1
• Date: Sun, 6 Jun 2021 14:57:17 GMT
• Title: Oriented Object Detection with Transformer
• Authors: Teli Ma, Mingyuan Mao, Honghui Zheng, Peng Gao, Xiaodi Wang, Shumin Han, Errui Ding, Baochang Zhang, David Doermann
• Abstract summary: We implement Oriented Object DEtection with TRansformer ($bf O2DETR$) based on an end-to-end network. We design a simple but highly efficient encoder for Transformer by replacing the attention mechanism with depthwise separable convolution. Our $rm O2DETR$ can be another new benchmark in the field of oriented object detection, which achieves up to 3.85 mAP improvement over Faster R-CNN and RetinaNet.
• Score: 51.634913687632604
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Object detection with Transformers (DETR) has achieved a competitive performance over traditional detectors, such as Faster R-CNN. However, the potential of DETR remains largely unexplored for the more challenging task of arbitrary-oriented object detection problem. We provide the first attempt and implement Oriented Object DEtection with TRansformer ($\bf O^2DETR$) based on an end-to-end network. The contributions of $\rm O^2DETR$ include: 1) we provide a new insight into oriented object detection, by applying Transformer to directly and efficiently localize objects without a tedious process of rotated anchors as in conventional detectors; 2) we design a simple but highly efficient encoder for Transformer by replacing the attention mechanism with depthwise separable convolution, which can significantly reduce the memory and computational cost of using multi-scale features in the original Transformer; 3) our $\rm O^2DETR$ can be another new benchmark in the field of oriented object detection, which achieves up to 3.85 mAP improvement over Faster R-CNN and RetinaNet. We simply fine-tune the head mounted on $\rm O^2DETR$ in a cascaded architecture and achieve a competitive performance over SOTA in the DOTA dataset.

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