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Zero Shot Segmentation

Papers

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Showing 51–100 of 134 papers

TitleStatusHype
The Emergence of Objectness: Learning Zero-Shot Segmentation from VideosCode1
TomoSAM: a 3D Slicer extension using SAM for tomography segmentationCode1
TongueSAM: An Universal Tongue Segmentation Model Based on SAM with Zero-ShotCode1
Training-free Object Counting with PromptsCode1
ZegOT: Zero-shot Segmentation Through Optimal Transport of Text PromptsCode1
Zero-Shot Edge Detection with SCESAME: Spectral Clustering-based Ensemble for Segment Anything Model EstimationCode1
Zero-Shot Tree Detection and Segmentation from Aerial Forest ImageryCode1
Exploring Open-Vocabulary Semantic Segmentation from CLIP Vision Encoder Distillation OnlyCode0
X-Recon: Learning-based Patient-specific High-Resolution CT Reconstruction from Orthogonal X-Ray ImagesCode0
HOLa: HoloLens Object LabelingCode0
Removing Watermarks with Partial Regeneration using Semantic InformationCode0
Unsupervised Deep Learning for Bayesian Brain MRI SegmentationCode0
Segment Anything in High QualityCode0
3D-PointZshotS: Geometry-Aware 3D Point Cloud Zero-Shot Semantic Segmentation Narrowing the Visual-Semantic GapCode0
Zero-Shot Segmentation of Eye Features Using the Segment Anything Model (SAM)Code0
PanSAM: Zero-Shot, Prompt-Free Pancreas Segmentation in CT ImagingCode0
SimSAM: Zero-shot Medical Image Segmentation via Simulated InteractionCode0
PaveCap: The First Multimodal Framework for Comprehensive Pavement Condition Assessment with Dense Captioning and PCI EstimationCode0
OpenSD: Unified Open-Vocabulary Segmentation and DetectionCode0
Quantifying the Limits of Segmentation Foundation Models: Modeling Challenges in Segmenting Tree-Like and Low-Contrast ObjectsCode0
Learning Zero-Shot Material States Segmentation, by Implanting Natural Image Patterns in Synthetic DataCode0
A Language-Guided Benchmark for Weakly Supervised Open Vocabulary Semantic SegmentationCode0
Prompt-and-Transfer: Dynamic Class-aware Enhancement for Few-shot Segmentation—0
Visual and Text Prompt Segmentation: A Novel Multi-Model Framework for Remote Sensing—0
Visual and Textual Prior Guided Mask Assemble for Few-Shot Segmentation and Beyond—0
Resilience of Vision Transformers for Domain Generalisation in the Presence of Out-of-Distribution Noisy Images—0
A Simple Framework for Open-Vocabulary Zero-Shot Segmentation—0
SAM 2 in Robotic Surgery: An Empirical Evaluation for Robustness and Generalization in Surgical Video Segmentation—0
SAM3D: Zero-Shot Semi-Automatic Segmentation in 3D Medical Images with the Segment Anything Model—0
SAM for Poultry Science—0
SAM-SP: Self-Prompting Makes SAM Great Again—0
SANeRF-HQ: Segment Anything for NeRF in High Quality—0
SAQ-SAM: Semantically-Aligned Quantization for Segment Anything Model—0
Segment Anything Meets Semantic Communication—0
Zero-shot spatial layout conditioning for text-to-image diffusion models—0
ZeroPS: High-quality Cross-modal Knowledge Transfer for Zero-Shot 3D Part Segmentation—0
Pedestrian Accessible Infrastructure Inventory: Assessing Zero-Shot Segmentation on Multi-Mode Geospatial Data for All Pedestrian Types—0
Segment Anything Model (SAM) for Digital Pathology: Assess Zero-shot Segmentation on Whole Slide Imaging—0
Segment to Recognize Robustly -- Enhancing Recognition by Image Decomposition—0
All-in-SAM: from Weak Annotation to Pixel-wise Nuclei Segmentation with Prompt-based Finetuning—0
Self-supervised Tumor Segmentation through Layer Decomposition—0
Show and Tell: Visually Explainable Deep Neural Nets via Spatially-Aware Concept Bottleneck Models—0
AlignZeg: Mitigating Objective Misalignment for Zero-shot Semantic Segmentation—0
SILC: Improving Vision Language Pretraining with Self-Distillation—0
SmartScan: An AI-based Interactive Framework for Automated Region Extraction from Satellite Images—0
SOS-Match: Segmentation for Open-Set Robust Correspondence Search and Robot Localization in Unstructured Environments—0
Exploring Open-Vocabulary Semantic Segmentation without Human Labels—0
Eye on the Target: Eye Tracking Meets Rodent Tracking—0
Few-Shot Adaptation of Training-Free Foundation Model for 3D Medical Image Segmentation—0
Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data—0
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All datasetsSegmentation in the WildADE20K training-free zero-shot segmentation

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Grounded HQ-SAMMean AP49.6—Unverified
2Grounded-SAMMean AP46—Unverified
3UNINEXTMean AP42.1—Unverified
4HIPIEMean AP41.6—Unverified
5SANMean AP41.4—Unverified
6odiseMean AP38.7—Unverified
7OpenSEEDMean AP36.1—Unverified
8OpenSDMean AP35.8—Unverified
9SGinW_Team (X-Decoder-L)Mean AP32.2—Unverified
10SGinW_Team (X-Decoder-B)Mean AP27.7—Unverified
#ModelMetricClaimedVerifiedStatus
1COSMOS ViT-B/16mIoU17.7—Unverified
2GEM (MetaCLIP)mIoU17.1—Unverified
3GEM (CLIP)mIoU15.7—Unverified
4CLIPSurgerymIoU12.9—Unverified
5MaskCLIPmIoU10.2—Unverified