Segmentation
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Benchmarks
Most implemented
U-Net: Convolutional Networks for Biomedical Image Segmentation
Mask R-CNN
Rethinking Atrous Convolution for Semantic Image Segmentation
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
Searching for MobileNetV3
Fully Convolutional Networks for Semantic Segmentation
Papers
SeC: Advancing Complex Video Object Segmentation via Progressive Concept Construction
Video Object Segmentation (VOS) is a core task in computer vision, requiring models to track and segment target objects across video frames. Despite notable advances with recent efforts, current techniques still lag behi…
ObjectSegmentationSemantic SegmentationVideo Object Segmentation+1Deep Learning-Based Fetal Lung Segmentation from Diffusion-weighted MRI Images and Lung Maturity Evaluation for Fetal Growth Restriction
Fetal lung maturity is a critical indicator for predicting neonatal outcomes and the need for post-natal intervention, especially for pregnancies affected by fetal growth restriction. Intra-voxel incoherent motion analys…
SegmentationDiffOSeg: Omni Medical Image Segmentation via Multi-Expert Collaboration Diffusion Model
Annotation variability remains a substantial challenge in medical image segmentation, stemming from ambiguous imaging boundaries and diverse clinical expertise. Traditional deep learning methods producing single determin…
Image SegmentationMedical Image SegmentationSegmentationSemantic SegmentationFrom Variability To Accuracy: Conditional Bernoulli Diffusion Models with Consensus-Driven Correction for Thin Structure Segmentation
Accurate segmentation of orbital bones in facial computed tomography (CT) images is essential for the creation of customized implants for reconstruction of defected orbital bones, particularly challenging due to the ambi…
Computed Tomography (CT)SegmentationUnleashing Vision Foundation Models for Coronary Artery Segmentation: Parallel ViT-CNN Encoding and Variational Fusion
Accurate coronary artery segmentation is critical for computeraided diagnosis of coronary artery disease (CAD), yet it remains challenging due to the small size, complex morphology, and low contrast with surrounding tiss…
Coronary Artery SegmentationSegmentationSCORE: Scene Context Matters in Open-Vocabulary Remote Sensing Instance Segmentation
Most existing remote sensing instance segmentation approaches are designed for close-vocabulary prediction, limiting their ability to recognize novel categories or generalize across datasets. This restricts their applica…
Earth ObservationInstance SegmentationSegmentationSemantic Segmentation