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A survey on label-efficient deep image segmentation: Bridging the gap between weak supervision and dense prediction
The rapid development of deep learning has made a great progress in image segmentation,
one of the fundamental tasks of computer vision. However, the current segmentation …
one of the fundamental tasks of computer vision. However, the current segmentation …
A survey on deep learning-based architectures for semantic segmentation on 2d images
Semantic segmentation is the pixel-wise labeling of an image. Boosted by the extraordinary
ability of convolutional neural networks (CNN) in creating semantic, high-level and …
ability of convolutional neural networks (CNN) in creating semantic, high-level and …
Transformer-based visual segmentation: A survey
Visual segmentation seeks to partition images, video frames, or point clouds into multiple
segments or groups. This technique has numerous real-world applications, such as …
segments or groups. This technique has numerous real-world applications, such as …
Freesolo: Learning to segment objects without annotations
Instance segmentation is a fundamental vision task that aims to recognize and segment
each object in an image. However, it requires costly annotations such as bounding boxes …
each object in an image. However, it requires costly annotations such as bounding boxes …
Bbam: Bounding box attribution map for weakly supervised semantic and instance segmentation
Weakly supervised segmentation methods using bounding box annotations focus on
obtaining a pixel-level mask from each box containing an object. Existing methods typically …
obtaining a pixel-level mask from each box containing an object. Existing methods typically …
Boxinst: High-performance instance segmentation with box annotations
We present a high-performance method that can achieve mask-level instance segmentation
with only bounding-box annotations for training. While this setting has been studied in the …
with only bounding-box annotations for training. While this setting has been studied in the …
C-cam: Causal cam for weakly supervised semantic segmentation on medical image
Recently, many excellent weakly supervised semantic segmentation (WSSS) works are
proposed based on class activation map** (CAM). However, there are few works that …
proposed based on class activation map** (CAM). However, there are few works that …
Pointly-supervised instance segmentation
We propose an embarrassingly simple point annotation scheme to collect weak supervision
for instance segmentation. In addition to bounding boxes, we collect binary labels for a set of …
for instance segmentation. In addition to bounding boxes, we collect binary labels for a set of …
H2RBox-v2: Incorporating symmetry for boosting horizontal box supervised oriented object detection
With the rapidly increasing demand for oriented object detection, eg in autonomous driving
and remote sensing, the recently proposed paradigm involving weakly-supervised detector …
and remote sensing, the recently proposed paradigm involving weakly-supervised detector …
Affinity attention graph neural network for weakly supervised semantic segmentation
Weakly supervised semantic segmentation is receiving great attention due to its low human
annotation cost. In this paper, we aim to tackle bounding box supervised semantic …
annotation cost. In this paper, we aim to tackle bounding box supervised semantic …