SOTAVerified

Semantic Segmentation

Papers

Showing 14761500 of 14763 papers

TitleStatusHype
DRU-net: An Efficient Deep Convolutional Neural Network for Medical Image SegmentationCode1
DecoupleNet: A Lightweight Backbone Network With Efficient Feature Decoupling for Remote Sensing Visual TasksCode1
Beyond Pixels: Enhancing LIME with Hierarchical Features and Segmentation Foundation ModelsCode1
Manhattan Room Layout Reconstruction from a Single 360 image: A Comparative Study of State-of-the-art MethodsCode1
AttaNet: Attention-Augmented Network for Fast and Accurate Scene ParsingCode1
DTBS: Dual-Teacher Bi-directional Self-training for Domain Adaptation in Nighttime Semantic SegmentationCode1
Dual-Attention GAN for Large-Pose Face FrontalizationCode1
A Generalized Deep Learning Framework for Whole-Slide Image Segmentation and AnalysisCode1
Automatic segmentation of spinal multiple sclerosis lesions: How to generalize across MRI contrasts?Code1
Dual-Domain Image Synthesis using Segmentation-Guided GANCode1
Dual Graph Convolutional Network for Semantic SegmentationCode1
A Generalized Framework for Video Instance SegmentationCode1
Dual Path Learning for Domain Adaptation of Semantic SegmentationCode1
MAPSeg: Unified Unsupervised Domain Adaptation for Heterogeneous Medical Image Segmentation Based on 3D Masked Autoencoding and Pseudo-LabelingCode1
Dual Super-Resolution Learning for Semantic SegmentationCode1
DC-SAM: In-Context Segment Anything in Images and Videos via Dual ConsistencyCode1
Duo-SegNet: Adversarial Dual-Views for Semi-Supervised Medical Image SegmentationCode1
DuSSS: Dual Semantic Similarity-Supervised Vision-Language Model for Semi-Supervised Medical Image SegmentationCode1
DVIS: Decoupled Video Instance Segmentation FrameworkCode1
Dynamic 3D Scene Analysis by Point Cloud AccumulationCode1
Dynamically Instance-Guided Adaptation: A Backward-Free Approach for Test-Time Domain Adaptive Semantic SegmentationCode1
Dynamic Dictionary Learning for Remote Sensing Image SegmentationCode1
Attention-based Transformation from Latent Features to Point CloudsCode1
DB-SAM: Delving into High Quality Universal Medical Image SegmentationCode1
DCSAU-Net: A Deeper and More Compact Split-Attention U-Net for Medical Image SegmentationCode1
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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
4InternImage-HValidation mIoU62.9Unverified
5M3I Pre-training (InternImage-H)Validation 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