SOTAVerified

Semantic Segmentation

Papers

Showing 42514275 of 14763 papers

TitleStatusHype
One Step Learning, One Step ReviewCode0
DILLEMA: Diffusion and Large Language Models for Multi-Modal AugmentationCode0
BLVD: Building A Large-scale 5D Semantics Benchmark for Autonomous DrivingCode0
Dilated-UNet: A Fast and Accurate Medical Image Segmentation Approach using a Dilated Transformer and U-Net ArchitectureCode0
One-Shot Medical Video Object Segmentation via Temporal Contrastive Memory NetworksCode0
One Shot Model For COVID-19 Classification and Lesions Segmentation In Chest CT Scans Using LSTM With Attention MechanismCode0
On the Optimal Combination of Cross-Entropy and Soft Dice Losses for Lesion Segmentation with Out-of-Distribution RobustnessCode0
Parameter Decoupling Strategy for Semi-supervised 3D Left Atrium SegmentationCode0
Dilated Residual NetworksCode0
Dilated Point Convolutions: On the Receptive Field Size of Point Convolutions on 3D Point CloudsCode0
Dilated deeply supervised networks for hippocampus segmentation in MRICode0
Dilated Convolutions with Lateral Inhibitions for Semantic Image SegmentationCode0
On Enhancing Brain Tumor Segmentation Across Diverse Populations with Convolutional Neural NetworksCode0
Dilated Continuous Random Field for Semantic SegmentationCode0
On Boosting Semantic Street Scene Segmentation with Weak SupervisionCode0
BlitzNet: A Real-Time Deep Network for Scene UnderstandingCode0
Adaptive Distillation: Aggregating Knowledge from Multiple Paths for Efficient DistillationCode0
One-pass Multi-task Networks with Cross-task Guided Attention for Brain Tumor SegmentationCode0
Diffusion Model for Camouflaged Object DetectionCode0
OmniDet: Surround View Cameras based Multi-task Visual Perception Network for Autonomous DrivingCode0
Black-box Unsupervised Domain Adaptation with Bi-directional Atkinson-Shiffrin MemoryCode0
OMEGAS: Object Mesh Extraction from Large Scenes Guided by Gaussian SegmentationCode0
Diffusion-Based Semantic Segmentation of Lumbar Spine MRI Scans of Lower Back Pain PatientsCode0
Blackbox Adaptation for Medical Image SegmentationCode0
An application of cascaded 3D fully convolutional networks for medical image segmentationCode0
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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