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 · We propose a noise-resistant training framework for learning object detectors from noisy annotations with entangled label noise and bounding box noise.
To summarize, this paper proposes a noise-resistant learning framework to train object detectors with noisy annotations. The proposed framework jointly ...
Secondly, these methods are designed for datasets that are corrupted by class-conditional noise between foreground categories with approximately balanced ...
Mar 3, 2020 · This work addresses the challenging problem of training object detectors with noisy annotations, where the noise contains a mixture of label ...
Mar 3, 2020 · To summarize, this paper proposes a noise-resistant learning framework to train object detectors with noisy annotations, where label noise and ...
We propose a learning framework which jointly optimizes object labels, bounding box coordinates, and model parameters by performing alternating noise correction ...
The Appendix contains following sections: Appendix A is the proof of the first order approximation of gradient reconcilement.
Missing: resistant | Show results with:resistant
"Universal Noise Annotation: Unveiling the Impact of Noisy Annotation on Object Detection. ... "Towards Noise-resistant Object Detection with Noisy Annotations." ...
Noisy Annotation Refinement for Object Detection - BMVC 2021
www.bmvc2021-virtualconference.com › ...
Our proposed method efficiently decouples the entangled noises, corrects the noisy annotations, and subsequently trains the detector using the corrected ...