SOTAVerified

Semantic Segmentation

Papers

Showing 226250 of 14763 papers

TitleStatusHype
Alleviating Textual Reliance in Medical Language-guided Segmentation via Prototype-driven Semantic ApproximationCode2
DaCapo: a modular deep learning framework for scalable 3D image segmentationCode2
Diving into Underwater: Segment Anything Model Guided Underwater Salient Instance Segmentation and A Large-scale DatasetCode2
Exact: Exploring Space-Time Perceptive Clues for Weakly Supervised Satellite Image Time Series Semantic SegmentationCode2
Exploring CLIP's Dense Knowledge for Weakly Supervised Semantic SegmentationCode2
DiverGen: Improving Instance Segmentation by Learning Wider Data Distribution with More Diverse Generative DataCode2
Distribution-Free, Risk-Controlling Prediction SetsCode2
An Empirical Study of Remote Sensing PretrainingCode2
FastInst: A Simple Query-Based Model for Real-Time Instance SegmentationCode2
Diversified and Personalized Multi-rater Medical Image SegmentationCode2
An Image is Worth 16x16 Words: Transformers for Image Recognition at ScaleCode2
Does Image Anonymization Impact Computer Vision Training?Code2
Feature 3DGS: Supercharging 3D Gaussian Splatting to Enable Distilled Feature FieldsCode2
DI-MaskDINO: A Joint Object Detection and Instance Segmentation ModelCode2
Dilated Neighborhood Attention TransformerCode2
FM-Fusion: Instance-aware Semantic Mapping Boosted by Vision-Language Foundation ModelsCode2
FocalClick: Towards Practical Interactive Image SegmentationCode2
FreeSOLO: Learning to Segment Objects without AnnotationsCode2
3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image SegmentationCode2
From SAM to CAMs: Exploring Segment Anything Model for Weakly Supervised Semantic SegmentationCode2
Frozen CLIP: A Strong Backbone for Weakly Supervised Semantic SegmentationCode2
DINO in the Room: Leveraging 2D Foundation Models for 3D SegmentationCode2
GeminiFusion: Efficient Pixel-wise Multimodal Fusion for Vision TransformerCode2
Diffusion models as plug-and-play priorsCode2
Digital Twin Generation from Visual Data: A SurveyCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1InternImage-H (M3I Pre-training)Params (M)1,310Unverified
2ViT-P (InternImage-H)Validation mIoU63.6Unverified
3ONE-PEACEValidation mIoU63Unverified
4M3I Pre-training (InternImage-H)Validation mIoU62.9Unverified
5InternImage-HValidation mIoU62.9Unverified
6BEiT-3Validation mIoU62.8Unverified
7EVAValidation mIoU62.3Unverified
8ViT-P (OneFormer, InternImage-H)Validation mIoU61.6Unverified
9ViT-Adapter-L (Mask2Former, BEiTv2 pretrain)Validation mIoU61.5Unverified
10FD-SwinV2-GValidation mIoU61.4Unverified