SOTAVerified

Semantic Segmentation

Papers

Showing 33513375 of 14763 papers

TitleStatusHype
EfficientPS: Efficient Panoptic SegmentationCode1
BT-Unet: A self-supervised learning framework for biomedical image segmentation using Barlow Twins with U-Net modelsCode1
Efficient Connectivity-Preserving Instance Segmentation with Supervoxel-Based Loss FunctionCode1
Reciprocal Transformations for Unsupervised Video Object SegmentationCode1
BSNet: Box-Supervised Simulation-assisted Mean Teacher for 3D Instance SegmentationCode1
DC-SAM: In-Context Segment Anything in Images and Videos via Dual ConsistencyCode1
DCSAU-Net: A Deeper and More Compact Split-Attention U-Net for Medical Image SegmentationCode1
DCSEG: Decoupled 3D Open-Set Segmentation using Gaussian SplattingCode1
DCT-Mask: Discrete Cosine Transform Mask Representation for Instance SegmentationCode1
1st Place Solution for MeViS Track in CVPR 2024 PVUW Workshop: Motion Expression guided Video SegmentationCode1
DC-UNet: Rethinking the U-Net Architecture with Dual Channel Efficient CNN for Medical Images SegmentationCode1
DDANet: Dual Decoder Attention Network for Automatic Polyp SegmentationCode1
Re-distributing Biased Pseudo Labels for Semi-supervised Semantic Segmentation: A Baseline InvestigationCode1
Reducing Information Bottleneck for Weakly Supervised Semantic SegmentationCode1
Ref-Diff: Zero-shot Referring Image Segmentation with Generative ModelsCode1
Effective semantic segmentation in Cataract Surgery: What matters most?Code1
Effect of Prior-based Losses on Segmentation Performance: A BenchmarkCode1
EditGAN: High-Precision Semantic Image EditingCode1
DEAL: Difficulty-aware Active Learning for Semantic SegmentationCode1
Diffusion Model is Secretly a Training-free Open Vocabulary Semantic SegmenterCode1
DeBiFormer: Vision Transformer with Deformable Agent Bi-level Routing AttentionCode1
Aligning Generative Denoising with Discriminative Objectives Unleashes Diffusion for Visual PerceptionCode1
Refine and Represent: Region-to-Object Representation LearningCode1
RefineMask: Towards High-Quality Instance Segmentation with Fine-Grained FeaturesCode1
EEEA-Net: An Early Exit Evolutionary Neural Architecture SearchCode1
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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