SOTAVerified

One-Shot Segmentation

( Image credit: One-Shot Learning for Semantic Segmentation )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–10 of 35 papers

TitleStatusHype
DC-SAM: In-Context Segment Anything in Images and Videos via Dual ConsistencyCode1
Federated Self-Supervised Learning for One-Shot Cross-Modal and Cross-Imaging Technique Segmentation—0
Data Adaptive Few-shot Multi Label Segmentation with Foundation Model—0
Correlation Weighted Prototype-based Self-Supervised One-Shot Segmentation of Medical Images—0
One Shot is Enough for Sequential Infrared Small Target SegmentationCode0
Dense Self-Supervised Learning for Medical Image Segmentation—0
Deep ContourFlow: Advancing Active Contours with Deep LearningCode1
CycleSAM: One-Shot Surgical Scene Segmentation using Cycle-Consistent Feature Matching to Prompt SAM—0
Non-Adversarial Learning: Vector-Quantized Common Latent Space for Multi-Sequence MRICode1
NubbleDrop: A Simple Way to Improve Matching Strategy for Prompted One-Shot Segmentation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MaskNetIoU [32 distractors]65.6—Unverified
2Siamese-U-NetIoU [32 distractors]62.4—Unverified