Mar 3, 2020 · We address the challenging problem of training object detectors with noisy annotations, where the noise contains a mixture of label noise and bounding box ...

Sep 28, 2020 · Our method achieves state-of-the-art performance by effectively cleaning both label noise and bounding box noise. One-sentence Summary: We ...

To summarize, this paper proposes a noise-resistant learning framework to train object detectors with noisy annotations. The proposed framework jointly ...

To address the critical yet undeveloped noisy DAOD issue, we propose a novel Noise Latent Transferability. Exploration (NLTE) framework to simultaneously ...

Mar 3, 2020 · This work addresses the challenging problem of training object detectors with noisy annotations, where the noise contains a mixture of label ...

Sep 7, 2024 · We address the challenging problem of training object detectors with noisy annotations, where the noise contains a mixture of label noise and ...

"Universal Noise Annotation: Unveiling the Impact of Noisy Annotation on Object Detection. ... "Towards Noise-resistant Object Detection with Noisy Annotations." ...

However, datasets obtained by these methods tend to contain noisy annotations such as inaccurate bounding boxes and incorrect class labels. In this study, we ...

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.

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