SOTAVerified

Zero Shot Segmentation

Papers

Showing 101134 of 134 papers

TitleStatusHype
Segment Anything in High QualityCode0
Exploring Open-Vocabulary Semantic Segmentation without Human Labels0
PaintSeg: Training-free Segmentation via PaintingCode1
One-Prompt to Segment All Medical ImagesCode1
SAM for Poultry Science0
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
Computer-Vision Benchmark Segment-Anything Model (SAM) in Medical Images: Accuracy in 12 Datasets0
A Closer Look at the Explainability of Contrastive Language-Image Pre-trainingCode1
SAM vs BET: A Comparative Study for Brain Extraction and Segmentation of Magnetic Resonance Images using Deep Learning0
Segment Anything Model (SAM) for Digital Pathology: Assess Zero-shot Segmentation on Whole Slide Imaging0
A Simple Framework for Open-Vocabulary Segmentation and DetectionCode3
Universal Instance Perception as Object Discovery and RetrievalCode3
Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object DetectionCode5
Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion ModelsCode2
A Language-Guided Benchmark for Weakly Supervised Open Vocabulary Semantic SegmentationCode0
Side Adapter Network for Open-Vocabulary Semantic SegmentationCode2
ZegOT: Zero-shot Segmentation Through Optimal Transport of Text PromptsCode1
Open-vocabulary Object Segmentation with Diffusion ModelsCode1
Exploring Open-Vocabulary Semantic Segmentation from CLIP Vision Encoder Distillation OnlyCode0
Generalized Decoding for Pixel, Image, and LanguageCode3
Open Vocabulary Semantic Segmentation with Patch Aligned Contrastive LearningCode1
Learning to Generate Text-grounded Mask for Open-world Semantic Segmentation from Only Image-Text PairsCode1
Open-world Semantic Segmentation via Contrasting and Clustering Vision-Language Embedding0
Language-driven Semantic SegmentationCode2
Image Segmentation Using Text and Image PromptsCode1
Extract Free Dense Labels from CLIPCode1
3D Compositional Zero-shot Learning with DeCompositional Consensus0
The Emergence of Objectness: Learning Zero-Shot Segmentation from VideosCode1
Self-supervised Tumor Segmentation through Layer Decomposition0
Consistent Structural Relation Learning for Zero-Shot Segmentation0
Context-aware Feature Generation for Zero-shot Semantic SegmentationCode1
Unsupervised Deep Learning for Bayesian Brain MRI SegmentationCode0
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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