Partial annotations in active learning for semantic segmentation

This paper addresses the challenge of efficiently training deep learning models for semantic segmentation with a limited set of annotated data.

(PDF) Partial annotations in active learning for semantic segmentation

The results show that partial annotations within an active learning framework can significantly improve efficiency in deep learning, especially ...

Publisher. Elsevier ; Subject. Active learning; Semantic segmentation; Deep learning; Partial annotation; Crack segmentation; Corrosion segmentation; Facade ...

Partial annotations in active learning for semantic segmentation

Partial annotations in active learning for semantic segmentation · B.G. Pantoja-Rosero · A. Chassignet · A. Rezaie · M. Kozinski · R. Achanta · K. Beyer.

Partial annotation for deep learning semantic segmentation

Partial annotation for deep learning semantic segmentation · Sketchpose: Learning to Segment Cells with Partial Annotations · Related Topics ...

Active Learning for Semantic Segmentation with Multi-class Label ...

We thus propose a new algorithm for learning semantic segmentation while disambiguating the partial labels in two stages. In the first stage ...

Bryan German Pantoja-Rosero on LinkedIn

Happy to share my most recent paper: "Partial Annotations in Active Learning for Semantic Segmentation" https://lnkd.in/e4z7vtex We ...

Proposed active learning framework for semantic segmentation.

Rather than requiring full annotations for all images, our method leverages partial annotations guided by predictions and uncertainty measures from previously ...

Data-efficient Active Learning for Structured Prediction with Partial ...

Manual annotation is requested only for the uncer- tain sub-structures (red), whereas model predictions can be used to annotate the highly- ...

Revision History for Active Learning for Semantic... - OpenReview

We thus propose a new algorithm for learning semantic segmentation while disambiguating the partial labels in two stages. In the first stage, it trains a ...

Official repository of the "Active Learning for Semantic Segmentation ...

This paper proposes a new active learning method for semantic segmentation. The core of our method lies in a new annotation query design.

Active Learning for Semantic Segmentation with Multi-class Label ...

algorithm for learning semantic segmentation while disambiguating the partial ... Suggestive annotation: A deep active learning framework for biomedical image ...

Semantic Segmentation With Active Semi-Supervised Learning

Figure 1: Our active learning approach aims to minimize the number of manual region annotations by using pseudo labels for unlabeled data during training phase.

Efficient Image Annotation for Semantic Segmentation

• Estimate annotation difficulty and training signal from image content. • Active learning pipeline. • Per-block labels instead of per-image labels. • Can ...

Partial Image Active Annotation (PIAA): An Efficient Active Learning ...

At first, we train our OCT semantic segmentation model by selecting a small, random subset of labeled data , which is used as the seed set. The ...

Active Learning for Semantic Segmentation | SuperAnnotate

We applied several active learning algorithms to select a part of the cityscapes dataset to be annotated and trained the “Dilated Residual ...

HAL-IA: A Hybrid Active Learning framework using Interactive ...

Active learning can reduce the annotation cost of image segmentation, but it faces three challenges: the cold start problem, an effective sample selection ...

Region-Based Active Learning for Efficient Labelling in Semantic ...

Annotations for Segmentation. ~ 1.5 to 2 hours for fine annotation ... partial annotation with active learning). Mapillary - 18000 unlabeled images ...

[PDF] Active learning for semantic segmentation with expected change

A novel active learning method specifically suited for semantic segmentation of pixels in an image according to the semantic class it belongs to, ...

Adaptive Superpixel for Active Learning in Semantic Segmentation

(d) As the round progresses, adaptive superpixels look similar to oracle ones. ical in practice as it determines the actual annotation cost such as the number ...