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Semantic Segmentation

Papers

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Showing 2576–2600 of 14763 papers

TitleStatusHype
TotalVibeSegmentator: Full Body MRI Segmentation for the NAKO and UK BiobankCode2
Extreme Point Supervised Instance Segmentation—0
Revisiting and Maximizing Temporal Knowledge in Semi-supervised Semantic SegmentationCode1
Uncertainty Quantification for Bird's Eye View Semantic Segmentation: Methods and Benchmarks—0
P-MSDiff: Parallel Multi-Scale Diffusion for Remote Sensing Image SegmentationCode0
CRIS: Collaborative Refinement Integrated with Segmentation for Polyp Segmentation—0
MCDS-VSS: Moving Camera Dynamic Scene Video Semantic Segmentation by Filtering with Self-Supervised Geometry and MotionCode0
Twin Deformable Point Convolutions for Point Cloud Semantic Segmentation in Remote Sensing Scenes—0
DenseSeg: Joint Learning for Semantic Segmentation and Landmark Detection Using Dense Image-to-Shape RepresentationCode0
Open-Set Domain Adaptation for Semantic SegmentationCode2
View-Consistent Hierarchical 3D Segmentation Using Ultrametric Feature FieldsCode0
Scaling White-Box Transformers for Vision—0
FMARS: Annotating Remote Sensing Images for Disaster Management using Foundation ModelsCode0
OpenDAS: Open-Vocabulary Domain Adaptation for 2D and 3D Segmentation—0
A Point-Neighborhood Learning Framework for Nasal Endoscope Image Segmentation—0
SemFlow: Binding Semantic Segmentation and Image Synthesis via Rectified FlowCode1
Enabling Visual Recognition at Radio Frequency—0
Organizing Background to Explore Latent Classes for Incremental Few-shot Semantic Segmentation—0
Lifelong Learning Using a Dynamically Growing Tree of Sub-networks for Domain Generalization in Video Object Segmentation—0
A Good Foundation is Worth Many Labels: Label-Efficient Panoptic SegmentationCode1
Optimizing Split Points for Error-Resilient SplitFed Learning—0
Reasoning3D -- Grounding and Reasoning in 3D: Fine-Grained Zero-Shot Open-Vocabulary 3D Reasoning Part Segmentation via Large Vision-Language Models—0
CBAR‑UNet: A novel methodology for segmentation of cardiac magnetic resonance images using block attention‑based deep residual neural networkCode0
Parameter-efficient Fine-tuning in Hyperspherical Space for Open-vocabulary Semantic Segmentation—0
The Binary Quantized Neural Network for Dense Prediction via Specially Designed Upsampling and Attention—0
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All datasetsADE20KNYU-Depth V2Cityscapes testCityscapes valADE20K valPASCAL ContextS3DIS Area5PASCAL VOC 2012 testS3DISScanNetSUN-RGBDDensePASS

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1InternImage-H (M3I Pre-training)Params (M)1,310—Unverified
2ViT-P (InternImage-H)Validation mIoU63.6—Unverified
3ONE-PEACEValidation mIoU63—Unverified
4InternImage-HValidation mIoU62.9—Unverified
5M3I Pre-training (InternImage-H)Validation mIoU62.9—Unverified
6BEiT-3Validation mIoU62.8—Unverified
7EVAValidation mIoU62.3—Unverified
8ViT-P (OneFormer, InternImage-H)Validation mIoU61.6—Unverified
9ViT-Adapter-L (Mask2Former, BEiTv2 pretrain)Validation mIoU61.5—Unverified
10FD-SwinV2-GValidation mIoU61.4—Unverified