SOTAVerified

Semantic Segmentation

Papers

Showing 30013025 of 14763 papers

TitleStatusHype
Attention-Based Transformers for Instance Segmentation of Cells in MicrostructuresCode1
FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene UnderstandingCode1
Flood Segmentation on Sentinel-1 SAR Imagery with Semi-Supervised LearningCode1
Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention NetworksCode1
Flow-based Video Segmentation for Human Head and ShouldersCode1
FLOSS: Free Lunch in Open-vocabulary Semantic SegmentationCode1
DC-UNet: Rethinking the U-Net Architecture with Dual Channel Efficient CNN for Medical Images SegmentationCode1
Data-Free Quantization Through Weight Equalization and Bias CorrectionCode1
CAMS: Convolution and Attention-Free Mamba-based Cardiac Image SegmentationCode1
Attention-guided Context Feature Pyramid Network for Object DetectionCode1
FNA++: Fast Network Adaptation via Parameter Remapping and Architecture SearchCode1
DatasetGAN: Efficient Labeled Data Factory with Minimal Human EffortCode1
DecoupleNet: A Lightweight Backbone Network With Efficient Feature Decoupling for Remote Sensing Visual TasksCode1
Focal Attention for Long-Range Interactions in Vision TransformersCode1
Large-scale 6D Object Pose Estimation Dataset for Industrial Bin-PickingCode1
FocalUNETR: A Focal Transformer for Boundary-aware Segmentation of CT ImagesCode1
Part2Object: Hierarchical Unsupervised 3D Instance SegmentationCode1
Part-aware Prototype Network for Few-shot Semantic SegmentationCode1
AggMask: Exploring locally aggregated learning of mask representations for instance segmentationCode1
Large Separable Kernel Attention: Rethinking the Large Kernel Attention Design in CNNCode1
Cooperative Self-Training for Multi-Target Adaptive Semantic SegmentationCode1
Cooperative Training and Latent Space Data Augmentation for Robust Medical Image SegmentationCode1
Learning in the Frequency DomainCode1
3D Medical Image Segmentation with Sparse Annotation via Cross-Teaching between 3D and 2D NetworksCode1
Lidar Panoptic Segmentation and Tracking without Bells and WhistlesCode1
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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