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Semantic Segmentation

Papers

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Showing 9101–9125 of 14763 papers

TitleStatusHype
Medical Image Segmentation via Sparse Coding Decoder—0
Medical Image Segmentation with Belief Function Theory and Deep Learning—0
Medical image segmentation with imperfect 3D bounding boxes—0
Medical Image Segmentation with Limited Supervision: A Review of Deep Network Models—0
Medical Image Segmentation with SAM-generated Annotations—0
Medical Report Generation based on Segment-Enhanced Contrastive Representation Learning—0
Medical Semantic Segmentation with Diffusion Pretrain—0
Medical Visual Prompting (MVP): A Unified Framework for Versatile and High-Quality Medical Image Segmentation—0
Preventing Unauthorized AI Over-Analysis by Medical Image Adversarial Watermarking—0
MedMAP: Promoting Incomplete Multi-modal Brain Tumor Segmentation with Alignment—0
MEDOE: A Multi-Expert Decoder and Output Ensemble Framework for Long-tailed Semantic Segmentation—0
MedPrompt: LLM-CNN Fusion with Weight Routing for Medical Image Segmentation and Classification—0
MedSAGa: Few-shot Memory Efficient Medical Image Segmentation using Gradient Low-Rank Projection in SAM—0
MedSAM-CA: A CNN-Augmented ViT with Attention-Enhanced Multi-Scale Fusion for Medical Image Segmentation—0
MedSAM-U: Uncertainty-Guided Auto Multi-Prompt Adaptation for Reliable MedSAM—0
MedSegDiffNCA: Diffusion Models With Neural Cellular Automata for Skin Lesion Segmentation—0
MedSegNet10: A Publicly Accessible Network Repository for Split Federated Medical Image Segmentation—0
MedSeg-R: Medical Image Segmentation with Clinical Reasoning—0
MedSeg-R: Reasoning Segmentation in Medical Images with Multimodal Large Language Models—0
MedVisionLlama: Leveraging Pre-Trained Large Language Model Layers to Enhance Medical Image Segmentation—0
MED-VT++: Unifying Multimodal Learning with a Multiscale Encoder-Decoder Video Transformer—0
Memory Aggregation Networks for Efficient Interactive Video Object Segmentation—0
Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation—0
Memory Based Video Scene Parsing—0
Memory Consistent Unsupervised Off-the-Shelf Model Adaptation for Source-Relaxed Medical Image Segmentation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1InternImage-H (M3I Pre-training)Params (M)1,310—Unverified
2ViT-P (InternImage-H)Validation mIoU63.6—Unverified
3ONE-PEACEValidation mIoU63—Unverified
4InternImage-HValidation mIoU62.9—Unverified
5M3I Pre-training (InternImage-H)Validation mIoU62.9—Unverified
6BEiT-3Validation mIoU62.8—Unverified
7EVAValidation mIoU62.3—Unverified
8ViT-P (OneFormer, InternImage-H)Validation mIoU61.6—Unverified
9ViT-Adapter-L (Mask2Former, BEiTv2 pretrain)Validation mIoU61.5—Unverified
10FD-SwinV2-GValidation mIoU61.4—Unverified