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 4901–4950 of 5035 papers

TitleStatusHype
Open Compound Domain Adaptation with Object Style Compensation for Semantic Segmentation—0
OpenNeRF: Open Set 3D Neural Scene Segmentation with Pixel-Wise Features and Rendered Novel Views—0
Open Source Infrastructure for Automatic Cell Segmentation—0
Open Vocabulary Multi-Label Video Classification—0
Open-vocabulary Panoptic Segmentation with Embedding Modulation—0
OpenWorldSAM: Extending SAM2 for Universal Image Segmentation with Language Prompts—0
Optical Character Recognition using Convolutional Neural Networks for Ashokan Brahmi Inscriptions—0
Optimal Decision-Making in Mixed-Agent Partially Observable Stochastic Environments via Reinforcement Learning—0
Optimal Decisions from Probabilistic Models: The Intersection-over-Union Case—0
Optimal Latent Vector Alignment for Unsupervised Domain Adaptation in Medical Image Segmentation—0
Optimal Multi-Object Segmentation with Novel Gradient Vector Flow Based Shape Priors—0
Optimal Surface Segmentation with Convex Priors in Irregularly Sampled Space—0
Optimization for Medical Image Segmentation: Theory and Practice when evaluating with Dice Score or Jaccard Index—0
Optimization of MedSAM model based on bounding box adaptive perturbation algorithm—0
Optimized Hybrid Focal Margin Loss for Crack Segmentation—0
Optimizing Edge Detection for Image Segmentation with Multicut Penalties—0
Optimizing Expected Intersection-Over-Union With Candidate-Constrained CRFs—0
Optimizing Split Points for Error-Resilient SplitFed Learning—0
Organ At Risk Segmentation with Multiple Modality—0
Organ-aware Multi-scale Medical Image Segmentation Using Text Prompt Engineering—0
Organ Segmentation From Full-size CT Images Using Memory-Efficient FCN—0
Oriented Light-Field Windows for Scene Flow—0
OR-UNet: an Optimized Robust Residual U-Net for Instrument Segmentation in Endoscopic Images—0
Osteoporosis Prediction from Hand and Wrist X-rays using Image Segmentation and Self-Supervised Learning—0
Osteoporosis Prediction from Hand X-ray Images Using Segmentation-for-Classification and Self-Supervised Learning—0
Otsu based Differential Evolution Method for Image Segmentation—0
Outline Objects using Deep Reinforcement Learning—0
Out-of-Distribution Detection in Multi-Label Datasets using Latent Space of β-VAE—0
Overcoming Data Scarcity in Scanning Tunnelling Microscopy Image Segmentation—0
OVFoodSeg: Elevating Open-Vocabulary Food Image Segmentation via Image-Informed Textual Representation—0
P3Net: Progressive and Periodic Perturbation for Semi-Supervised Medical Image Segmentation—0
PAANet: Progressive Alternating Attention for Automatic Medical Image Segmentation—0
PADDIT: Probabilistic Augmentation of Data using Diffeomorphic Image Transformation—0
PaddleSeg: A High-Efficient Development Toolkit for Image Segmentation—0
Palette-based Color Transfer between Images—0
Pallet Detection from Synthetic Data Using Game Engines—0
Panoptic-Depth Color Map for Combination of Depth and Image Segmentation—0
PAN: Projective Adversarial Network for Medical Image Segmentation—0
Parallel Multi-Dimensional LSTM, With Application to Fast Biomedical Volumetric Image Segmentation—0
Parallel Watershed Partitioning: GPU-Based Hierarchical Image Segmentation—0
Parallel WiSARD object tracker: a ram-based tracking system—0
Parameter Efficient Fine-tuning via Cross Block Orchestration for Segment Anything Model—0
Parameter-Efficient Transformer with Hybrid Axial-Attention for Medical Image Segmentation—0
Parameter Learning for Log-supermodular Distributions—0
Parametric Image Segmentation of Humans with Structural Shape Priors—0
Parametric Imaging of FDG-PET Data Using Physiology and Iterative Regularization: Application to the Hepatic and Renal Systems—0
PARF-Net: integrating pixel-wise adaptive receptive fields into hybrid Transformer-CNN network for medical image segmentation—0
Segmentation of Parotid Gland Tumors Using Multimodal MRI and Contrastive Learning—0
Partial Labeled Gastric Tumor Segmentation via patch-based Reiterative Learning—0
Partially Supervised Unpaired Multi-Modal Learning for Label-Efficient Medical Image Segmentation—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