SOTAVerified

Zero Shot Segmentation

Papers

Showing 2650 of 134 papers

TitleStatusHype
COSMOS: Cross-Modality Self-Distillation for Vision Language Pre-trainingCode1
Evaluation Study on SAM 2 for Class-agnostic Instance-level SegmentationCode1
SAM-UNet:Enhancing Zero-Shot Segmentation of SAM for Universal Medical ImagesCode1
MeshSegmenter: Zero-Shot Mesh Semantic Segmentation via Texture SynthesisCode1
Frenet-Serret Frame-based Decomposition for Part Segmentation of 3D Curvilinear StructuresCode1
TV-SAM: Increasing Zero-Shot Segmentation Performance on Multimodal Medical Images Using GPT-4 Generated Descriptive Prompts Without Human AnnotationCode1
MatSAM: Efficient Extraction of Microstructures of Materials via Visual Large ModelCode1
Spectral Prompt Tuning:Unveiling Unseen Classes for Zero-Shot Semantic SegmentationCode1
Grounding Everything: Emerging Localization Properties in Vision-Language TransformersCode1
GeoSAM: Fine-tuning SAM with Multi-Modal Prompts for Mobility Infrastructure SegmentationCode1
Learning Mask-aware CLIP Representations for Zero-Shot SegmentationCode1
MediViSTA: Medical Video Segmentation via Temporal Fusion SAM Adaptation for EchocardiographyCode1
Zero-Shot Edge Detection with SCESAME: Spectral Clustering-based Ensemble for Segment Anything Model EstimationCode1
TongueSAM: An Universal Tongue Segmentation Model Based on SAM with Zero-ShotCode1
Training-free Object Counting with PromptsCode1
How to Efficiently Adapt Large Segmentation Model(SAM) to Medical ImagesCode1
Primitive Generation and Semantic-related Alignment for Universal Zero-Shot SegmentationCode1
TomoSAM: a 3D Slicer extension using SAM for tomography segmentationCode1
PaintSeg: Training-free Segmentation via PaintingCode1
One-Prompt to Segment All Medical ImagesCode1
Segment Anything Model for Medical Images?Code1
Generalist Vision Foundation Models for Medical Imaging: A Case Study of Segment Anything Model on Zero-Shot Medical SegmentationCode1
Segment Anything Model for Medical Image Analysis: an Experimental StudyCode1
A Closer Look at the Explainability of Contrastive Language-Image Pre-trainingCode1
ZegOT: Zero-shot Segmentation Through Optimal Transport of Text PromptsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Grounded HQ-SAMMean AP49.6Unverified
2Grounded-SAMMean AP46Unverified
3UNINEXTMean AP42.1Unverified
4HIPIEMean AP41.6Unverified
5SANMean AP41.4Unverified
6odiseMean AP38.7Unverified
7OpenSEEDMean AP36.1Unverified
8OpenSDMean AP35.8Unverified
9SGinW_Team (X-Decoder-L)Mean AP32.2Unverified
10SGinW_Team (X-Decoder-B)Mean AP27.7Unverified
#ModelMetricClaimedVerifiedStatus
1COSMOS ViT-B/16mIoU17.7Unverified
2GEM (MetaCLIP)mIoU17.1Unverified
3GEM (CLIP)mIoU15.7Unverified
4CLIPSurgerymIoU12.9Unverified
5MaskCLIPmIoU10.2Unverified