SOTAVerified

Semantic Segmentation

Papers

Showing 29262950 of 14763 papers

TitleStatusHype
Off-Road LiDAR Intensity Based Semantic SegmentationCode1
ATOMMIC: An Advanced Toolbox for Multitask Medical Imaging Consistency to facilitate Artificial Intelligence applications from acquisition to analysis in Magnetic Resonance ImagingCode1
Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary CellsCode1
Ladder Fine-tuning approach for SAM integrating complementary networkCode1
Fast Object Segmentation Learning with Kernel-based Methods for RoboticsCode1
FastSAM-3DSlicer: A 3D-Slicer Extension for 3D Volumetric Segment Anything Model with Uncertainty QuantificationCode1
Fast Point TransformerCode1
D2Det: Towards High Quality Object Detection and Instance SegmentationCode1
Omni-supervised Point Cloud Segmentation via Gradual Receptive Field Component ReasoningCode1
Calibrated Adversarial Refinement for Stochastic Semantic SegmentationCode1
Fast-SNN: Fast Spiking Neural Network by Converting Quantized ANNCode1
D3RM: A Discrete Denoising Diffusion Refinement Model for Piano TranscriptionCode1
CalibNet: Dual-branch Cross-modal Calibration for RGB-D Salient Instance SegmentationCode1
D2Conv3D: Dynamic Dilated Convolutions for Object Segmentation in VideosCode1
A Transductive Approach for Video Object SegmentationCode1
Knowledge Distillation from 3D to Bird's-Eye-View for LiDAR Semantic SegmentationCode1
Fast Video Object Segmentation using the Global Context ModuleCode1
Knowledge Distillation from A Stronger TeacherCode1
FCCDN: Feature Constraint Network for VHR Image Change DetectionCode1
D2A U-Net: Automatic Segmentation of COVID-19 Lesions from CT Slices with Dilated Convolution and Dual Attention MechanismCode1
FCN-Transformer Feature Fusion for Polyp SegmentationCode1
3DLabelProp: Geometric-Driven Domain Generalization for LiDAR Semantic Segmentation in Autonomous DrivingCode1
Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR-based PerceptionCode1
D^2Conv3D: Dynamic Dilated Convolutions for Object Segmentation in VideosCode1
Cyclic Learning: Bridging Image-level Labels and Nuclei Instance 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
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