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

Showing 11511175 of 5035 papers

TitleStatusHype
Adaptive Patching for High-resolution Image Segmentation with Transformers0
Constructing and Exploring Intermediate Domains in Mixed Domain Semi-supervised Medical Image SegmentationCode2
LLM-Seg: Bridging Image Segmentation and Large Language Model ReasoningCode2
Practical Region-level Attack against Segment Anything ModelsCode0
Calibration & Reconstruction: Deep Integrated Language for Referring Image Segmentation0
Vision-Aware Text Features in Referring Image Segmentation: From Object Understanding to Context UnderstandingCode0
Practical Guidelines for Cell Segmentation Models Under Optical Aberrations in Microscopy0
A Mutual Inclusion Mechanism for Precise Boundary Segmentation in Medical ImagesCode0
GLID: Pre-training a Generalist Encoder-Decoder Vision Model0
Streamlined Photoacoustic Image Processing with Foundation Models: A Training-Free Solution0
Visual Context-Aware Person Fall DetectionCode0
Multi-view Aggregation Network for Dichotomous Image SegmentationCode2
LUCF-Net: Lightweight U-shaped Cascade Fusion Network for Medical Image SegmentationCode1
Multi-rater Prompting for Ambiguous Medical Image Segmentation0
An Evidential-enhanced Tri-Branch Consistency Learning Method for Semi-supervised Medical Image Segmentation0
O2V-Mapping: Online Open-Vocabulary Mapping with Neural Implicit Representation0
SAM-I-Am: Semantic Boosting for Zero-shot Atomic-Scale Electron Micrograph SegmentationCode0
EPL: Evidential Prototype Learning for Semi-supervised Medical Image Segmentation0
Uncertainty-aware Evidential Fusion-based Learning for Semi-supervised Medical Image Segmentation0
Test-Time Adaptation with SaLIP: A Cascade of SAM and CLIP for Zero shot Medical Image SegmentationCode2
GHOST: Grounded Human Motion Generation with Open Vocabulary Scene-and-Text Contexts0
Image-based Agarwood Resinous Area Segmentation using Deep Learning0
AlignZeg: Mitigating Objective Misalignment for Zero-shot Semantic Segmentation0
LHU-Net: A Light Hybrid U-Net for Cost-Efficient, High-Performance Volumetric Medical Image SegmentationCode2
FPL+: Filtered Pseudo Label-based Unsupervised Cross-Modality Adaptation for 3D Medical Image SegmentationCode1
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Benchmark Results

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