2019年3月9日 · In this paper, we employ weak mask representation for CNN in box-level tracking with only initial rough object rectangle given. We overcome the data deficiency challenge and successfully specialize a semantic model for a given object by online data augmentation.

2023年1月1日 · An online pseudo-mask correcting scheme is designed for weakly-supervised semantic segmentation (WSSS). Introducing robust loss functions and regularization techniques against noisy labels for WSSS. Proposing an EMA teacher network to correct noisy labels in the pseudo-masks for WSSS.

2024年11月26日 · This paper studies various weak losses for partially annotated data in combination with existing supervised losses. We propose Box-for-Mask and Mask-for-Box strategies, and their combination BoMBo, to distil necessary information from one task annotations to train the other.

2025年1月1日 · Thus, learning from imperfect annotations (e.g. noisy or weak annotations) has emerged as a prominent research area in medical image segmentation. This work aims to extract high-quality pseudo masks from imperfect annotations with the assistance of …

As a result, the output of CNN in our method, compared with that in classical semantic segmentation, is much more imprecise, thus we regard it as “weak mask”. To ensure efficiency, a common practice in the object tracking community is to apply a patch based method instead of processing on the whole frame [2, 3, 18].

2023年10月4日 · Weakly supervised semantic segmentation (WSSS) can obtain pseudo-semantic masks through a weaker level of supervised labels, reducing the need for costly pixel-level annotations.

2019年8月1日 · To address the limitation, we propose to take a binary mask as the output of CNN for tracking. To this end, we adapt a semantic segmentation model by online fine-tuning with augmented samples in the initial frame to uncover the target in the following frames.

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2023年6月1日 · In order to solve this problem, we suggest a network based on spatial sub-region feature extraction and mask-aware loss that can detect metal surface defects.

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2020年4月21日 · Even very weak masks (20% effective) can still be useful if the underlying transmission rate is relatively low or decreasing: In Washington, where baseline transmission is much less intense, 80% adoption of such masks could reduce mortality by 24-65% (and peak deaths 15-69%), compared to 2-9% mortality reduction in New York (peak death reduction...

2019年3月9日 · To address the limitation, we propose to take a binary mask as the output of CNN for tracking. To this end, we adapt a semantic segmentation model by online fine-tuning with augmented samples in the initial frame to uncover the target in the following frames.

Exploiting Weak Mask Representation with Convolutional Neural Networks for Accurate Object Tracking. Recent years have witnessed the popularity of Convolutional Neural Networks (CNN) in a variety of computer vision tasks, including video object tracking. Existing object.

To address the limitation, we propose to take a binary mask as the output of CNN for tracking. To this end, we adapt a semantic segmentation model by online fine-tuning with augmented samples in the initial frame to uncover the target in the following frames.

2019年8月1日 · To address the limitation, we propose to take a binary mask as the output of CNN for tracking. To this end, we adapt a semantic segmentation model by online fine-tuning with augmented samples in...

Even very weak masks (20% effective) can still be useful if the underlying transmission rate is relatively low or decreasing: In Washington, where baseline transmission is much less intense, 80% adoption of such masks could reduce mortality by 24–65% (and peak deaths 15–69%), compared to 2–9% mortality reduction in New York (peak death ...