Scribble-Supervised Video Object Segmentation
Sign Up to like & getrecommendations! Published in 2022 at "IEEE/CAA Journal of Automatica Sinica"
DOI: 10.1109/jas.2021.1004210
Abstract: Recently, video object segmentation has received great attention in the computer vision community. Most of the existing methods heavily rely on the pixel-wise human annotations, which are expensive and time-consuming to obtain. To tackle this… read more here.
Keywords: object segmentation; segmentation scribble; segmentation; scribble supervised ... See more keywords
Mutual Iterative Refinement Network for Scribble-Supervised Camouflaged Object Detection
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DOI: 10.1109/tip.2025.3629044
Abstract: Detecting camouflaged objects is challenging due to their high visual similarity to surrounding environments in texture, color, and shape. Traditional Camouflaged Object Detection (COD) methods heavily rely on pixel-level annotations, which are costly and time-consuming.… read more here.
Keywords: refinement; iterative refinement; object detection; camouflaged object ... See more keywords
ScribFormer: Transformer Makes CNN Work Better for Scribble-Based Medical Image Segmentation
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Medical Imaging"
DOI: 10.1109/tmi.2024.3363190
Abstract: Most recent scribble-supervised segmentation methods commonly adopt a CNN framework with an encoder-decoder architecture. Despite its multiple benefits, this framework generally can only capture small-range feature dependency for the convolutional layer with the local receptive… read more here.
Keywords: branch; segmentation; scribble supervised; supervised segmentation ... See more keywords
Shape-Aware Adversarial Learning for Scribble-Supervised Medical Image Segmentation with a MaskMix Siamese Network: A Case Study of Cardiac MRI Segmentation
Sign Up to like & getrecommendations! Published in 2024 at "Bioengineering"
DOI: 10.3390/bioengineering11111146
Abstract: The transition in medical image segmentation from fine-grained to coarse-grained annotation methods, notably scribble annotation, offers a practical and efficient preparation for deep learning applications. However, these methods often compromise segmentation precision and result in… read more here.
Keywords: segmentation; scribble supervised; medical image; image segmentation ... See more keywords