SOTAVerified

Semantic Segmentation

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 10701–10725 of 14763 papers

TitleStatusHype
Learning Debiased and Disentangled Representations for Semantic Segmentation—0
Learning Deep Representations for Semantic Image Parsing: a Comprehensive Overview—0
Learning Dense Convolutional Embeddings for Semantic Segmentation—0
Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes—0
Learning Discriminative Feature with CRF for Unsupervised Video Object Segmentation—0
Learning Discriminators as Energy Networks in Adversarial Learning—0
Learning Disentangled Representations of Satellite Image Time Series—0
Learning Disentangled Representations via Independent Subspaces—0
Learning Dynamic Hierarchical Models for Anytime Scene Labeling—0
Learning Explicit Object-Centric Representations with Vision Transformers—0
Learning Expressive Prompting With Residuals for Vision Transformers—0
Learning Feature Inversion for Multi-class Anomaly Detection under General-purpose COCO-AD Benchmark—0
Learning for Structured Prediction Using Approximate Subgradient Descent with Working Sets—0
Learning from Exemplars for Interactive Image Segmentation—0
Learning from Mistakes: Self-Regularizing Hierarchical Representations in Point Cloud Semantic Segmentation—0
Learning from Multimodal and Multitemporal Earth Observation Data for Building Damage Mapping—0
Multi-View Representation is What You Need for Point-Cloud Pre-Training—0
Learning from Partial Label Proportions for Whole Slide Image Segmentation—0
Learning from Partially Overlapping Labels: Image Segmentation under Annotation Shift—0
Learning from Pixel-Level Label Noise: A New Perspective for Semi-Supervised Semantic Segmentation—0
Learning from SAM: Harnessing a Foundation Model for Sim2Real Adaptation by Regularization—0
Learning from Synthetic Data: Addressing Domain Shift for Semantic Segmentation—0
M3Act: Learning from Synthetic Human Group Activities—0
Learning from THEODORE: A Synthetic Omnidirectional Top-View Indoor Dataset for Deep Transfer Learning—0
Learning From Weakly Supervised Data by The Expectation Loss SVM (e-SVM) algorithm—0
Show:102550
← PrevPage 429 of 591Next →
All datasetsADE20KNYU-Depth V2Cityscapes testCityscapes valADE20K valPASCAL ContextS3DIS Area5PASCAL VOC 2012 testS3DISScanNetSUN-RGBDDensePASS

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
4M3I Pre-training (InternImage-H)Validation mIoU62.9—Unverified
5InternImage-HValidation 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