In this study, we highlight a problem of object detection with noisy bounding box annotations and show that these noisy annotations are harmful to the ...

Oct 20, 2021 · Our proposed method efficiently decouples the entangled noises, corrects the noisy annotations, and subsequently trains the detector using the ...

In this study, we focus on training object detectors on datasets with noisy localization annotations (bounding boxes). We train Faster R-CNN as the baseline to ...

In this study, we propose a novel problem setting of training object detector on datasets with entangled classification noise and localization annotation noise.

In this study, we highlight a problem of object detection with noisy bounding box annotations and show that these noisy annotations are harmful to the ...

This study proposes a new problem setting of training object detectors on datasets with entangled noises of annotations of class labels and bounding boxes, ...

Our study motivates a new challenging task “refinement of noisy localization labels" and sets a first benchmark for Pascal VOC 2012.

In this study, we highlight a problem of object detection with noisy bounding box annotations and show that these noisy annotations are harmful to the ...

Dec 21, 2023 · In this paper, we propose Universal-Noise Annotation (UNA), a more practical setting that encompasses all types of noise that can occur in object detection.

It was performed by humans with various experiences which resulted in noisy annotations such as inaccurate bounding boxes and incorrect class labels. ... ...