May 11, 2021 · In this work, we present Scale-aware Domain Adaptive Faster R-CNN, a model aiming at improving the cross-domain robustness of object detection.

In this work, we present Scale-aware Domain Adaptive Faster R-CNN, a model aiming at improving the cross-domain robustness of object detection.

This is a PyTorch implementation of 'Domain Adaptive Faster R-CNN for Object Detection in the Wild', implemented by Haoran Wang(whrzxzero@gmail.com).

Dec 9, 2024 · In this paper, we propose a new approach called Unbiased Mean Teacher (UMT) for cross domain object detection. While the simple mean teacher (MT) ...

In this work, we present Scale-aware Domain Adaptive Faster R-CNN, a model aiming at improving the cross-domain robustness of object detection. In ...

In this work, we present Scale-aware Domain Adaptive Faster R-CNN, a model aiming at improving the cross-domain robustness of object detection.

This is a Caffe2 implementation of 'Domain Adaptive Faster R-CNN for Object Detection in the Wild', implemented by Haoran Wang(whrzxzero@gmail.com).

In this work, we present Scale-aware Domain Adaptive Faster R-CNN, a model aiming at improving the cross-domain robustness of object detection. In ...

We build an end-to-end deep learning model based on the state-of-the-art Faster R-CNN model [48], referred to as Domain Adaptive Faster R-CNN. Based on the ...

In this work, we present Scale-aware Domain Adaptive Faster R-CNN, a model aiming at improving the cross-domain robustn