SOTAVerified

Semantic Segmentation

Papers

Showing 20762100 of 14763 papers

TitleStatusHype
On Advantages of Mask-level Recognition for Outlier-aware SegmentationCode1
The CropAndWeed Dataset: A Multi-Modal Learning Approach for Efficient Crop and Weed ManipulationCode1
TarViS: A Unified Approach for Target-based Video SegmentationCode1
All in Tokens: Unifying Output Space of Visual Tasks via Soft TokenCode1
Reference Twice: A Simple and Unified Baseline for Few-Shot Instance SegmentationCode1
Medical Image Segmentation via Cascaded Attention DecodingCode1
TinyMIM: An Empirical Study of Distilling MIM Pre-trained ModelsCode1
Betrayed by Captions: Joint Caption Grounding and Generation for Open Vocabulary Instance SegmentationCode1
Label-Guided Knowledge Distillation for Continual Semantic Segmentation on 2D Images and 3D Point CloudsCode1
Video Object Segmentation-aware Video Frame InterpolationCode1
Single Domain Generalization for LiDAR Semantic SegmentationCode1
PeakConv: Learning Peak Receptive Field for Radar Semantic SegmentationCode1
WaterMask: Instance Segmentation for Underwater ImageryCode1
Towards Better Stability and Adaptability: Improve Online Self-Training for Model Adaptation in Semantic SegmentationCode1
Sparsely Annotated Semantic Segmentation With Adaptive Gaussian MixturesCode1
Multispectral Video Semantic Segmentation: A Benchmark Dataset and BaselineCode1
Uni-3D: A Universal Model for Panoptic 3D Scene ReconstructionCode1
Change-Aware Sampling and Contrastive Learning for Satellite ImagesCode1
Interactive Segmentation As Gaussion Process ClassificationCode1
Weakly Supervised Semantic Segmentation via Adversarial Learning of Classifier and ReconstructorCode1
Efficient Mask Correction for Click-Based Interactive Image SegmentationCode1
CDAC: Cross-domain Attention Consistency in Transformer for Domain Adaptive Semantic SegmentationCode1
Disentangle then Parse: Night-time Semantic Segmentation with Illumination DisentanglementCode1
Context-Aware Relative Object Queries To Unify Video Instance and Panoptic SegmentationCode1
Towards Reliable Medical Image Segmentation by utilizing Evidential Calibrated UncertaintyCode1
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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