SOTAVerified

Image Segmentation

Image Segmentation is a computer vision task that involves dividing an image into multiple segments or regions, each of which corresponds to a different object or part of an object. The goal of image segmentation is to assign a unique label or category to each pixel in the image, so that pixels with similar attributes are grouped together.

Papers

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Showing 4701–4750 of 5035 papers

TitleStatusHype
Utilizing Large Scale Vision and Text Datasets for Image Segmentation from Referring Expressions—0
A 4D Light-Field Dataset and CNN Architectures for Material Recognition—0
VoxResNet: Deep Voxelwise Residual Networks for Volumetric Brain SegmentationCode0
Parameter Learning for Log-supermodular Distributions—0
SSHMT: Semi-supervised Hierarchical Merge Tree for Electron Microscopy Image SegmentationCode0
The Importance of Skip Connections in Biomedical Image SegmentationCode0
Gaze2Segment: A Pilot Study for Integrating Eye-Tracking Technology into Medical Image Segmentation—0
Fractional Calculus In Image Processing: A Review—0
A combined Approach Based on Fuzzy Classification and Contextual Region Growing to Image Segmentation—0
Play and Learn: Using Video Games to Train Computer Vision Models—0
An efficient iterative thresholding method for image segmentationCode0
Interactive Image Segmentation Using Constrained Dominant Sets—0
HeMIS: Hetero-Modal Image SegmentationCode0
Adaptable Precomputation for Random Walker Image Segmentation and Registration—0
Screen Content Image Segmentation Using Robust Regression and Sparse Decomposition—0
Artificial neural networks and fuzzy logic for recognizing alphabet characters and mathematical symbols—0
Incorporating prior knowledge in medical image segmentation: a survey—0
Can we unify monocular detectors for autonomous driving by using the pixel-wise semantic segmentation of CNNs?—0
Geometry in Active Learning for Binary and Multi-class Image Segmentation—0
Interactive Image Segmentation From A Feedback Control Perspective—0
Disjunctive Normal Level Set: An Efficient Parametric Implicit Method—0
Detection and Tracking of Liquids with Fully Convolutional Networks—0
Slack and Margin Rescaling as Convex Extensions of Supermodular FunctionsCode0
ZNNi - Maximizing the Inference Throughput of 3D Convolutional Networks on Multi-Core CPUs and GPUs—0
V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image SegmentationCode0
Free Form based active contours for image segmentation and free space perception—0
Deep Learning Convolutional Networks for Multiphoton Microscopy Vasculature SegmentationCode0
An Interactive Medical Image Segmentation Framework Using Iterative Refinement—0
Better Image Segmentation by Exploiting Dense Semantic Predictions—0
Layered Scene Decomposition via the Occlusion-CRF—0
A New Finsler Minimal Path Model With Curvature Penalization for Image Segmentation and Closed Contour Detection—0
Speeding up Semantic Segmentation for Autonomous DrivingCode0
Scale-Aware Alignment of Hierarchical Image SegmentationCode0
Recurrent Fully Convolutional Networks for Video Segmentation—0
Interactive Segmentation on RGBD Images via Cue Selection—0
Discriminative Multi-Modal Feature Fusion for RGBD Indoor Scene Recognition—0
Active Image Segmentation Propagation—0
Joint Multiview Segmentation and Localization of RGB-D Images Using Depth-Induced Silhouette Consistency—0
The use of deep learning in image segmentation, classification and detection—0
Image segmentation based on the hybrid total variation model and the K-means clustering strategy—0
Real-Time Human Motion Capture with Multiple Depth Cameras—0
Natural Scene Image Segmentation Based on Multi-Layer Feature Extraction—0
Convolutional Random Walk Networks for Semantic Image Segmentation—0
A Formal Evaluation of PSNR as Quality Measurement Parameter for Image Segmentation Algorithms—0
Bridging Category-level and Instance-level Semantic Image Segmentation—0
Automated Resolution Selection for Image Segmentation—0
Superpixel HierarchyCode0
Hierarchical Piecewise-Constant Super-regions—0
Bacterial foraging optimization based brain magnetic resonance image segmentation—0
Image segmentation with superpixel-based covariance descriptors in low-rank representation—0
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All datasetsMSD (Mirror Segmentation Dataset)PMDMAS3KPascal Panoptic PartsRMASPASCAL VOCHuTu 80MARIDACOCO val2017ImageNetMSD HeartOxfordPets

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SAM2-UNetIoU0.92—Unverified
2HetNetIoU0.83—Unverified
3PMDIoU0.82—Unverified
4SANetIoU0.8—Unverified
5MirrorNetIoU0.79—Unverified
#ModelMetricClaimedVerifiedStatus
1SAM2-UNetIoU0.73—Unverified
2HetNetIoU0.69—Unverified
3SANetIoU0.67—Unverified
4PMDIoU0.66—Unverified
5MirrorNetIoU0.59—Unverified
#ModelMetricClaimedVerifiedStatus
1SAM2-UNetmIoU0.8—Unverified
2MAS-SAMmIoU0.79—Unverified
3MASNetmIoU0.74—Unverified
4ZoomNetmIoU0.74—Unverified
#ModelMetricClaimedVerifiedStatus
1HIPIE (ViT-H)mIoUPartS63.8—Unverified
2PPSmIoUPartS58.6—Unverified
3HIPIE (ResNet-50)mIoUPartS57.2—Unverified
4JPPFmIoUPartS54.4—Unverified
#ModelMetricClaimedVerifiedStatus
1MAS-SAMmIoU0.74—Unverified
2SAM2-UNetmIoU0.74—Unverified
3MASNetmIoU0.73—Unverified
4ZoomNetmIoU0.73—Unverified
#ModelMetricClaimedVerifiedStatus
1OneNete,4-CmIoU63.6—Unverified
2OneNete,4-SmAP0.552.75—Unverified
3OneNeted,4mIoU14.9—Unverified
#ModelMetricClaimedVerifiedStatus
1UNetRDice0.98—Unverified
2PALEDDice0.98—Unverified
#ModelMetricClaimedVerifiedStatus
1ResAttUNetIoU0.67—Unverified
2UNetIoU0.57—Unverified
#ModelMetricClaimedVerifiedStatus
1SynCo (ResNet-50) 200epmask AP35.4—Unverified
#ModelMetricClaimedVerifiedStatus
1MobileOne-S0GFLOPs0.28—Unverified
#ModelMetricClaimedVerifiedStatus
1OneNete,4mIoU6.6—Unverified
#ModelMetricClaimedVerifiedStatus
1OneNete,4-CDice Score0.97—Unverified