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Semantic Segmentation

Papers

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Showing 7451–7500 of 14763 papers

TitleStatusHype
PIDNet: A Real-time Semantic Segmentation Network Inspired by PID ControllersCode2
Occlusion-Resistant Instance Segmentation of Piglets in Farrowing Pens Using Center Clustering Network—0
R2U++: A Multiscale Recurrent Residual U-Net with Dense Skip Connections for Medical Image Segmentation—0
Mutual- and Self- Prototype Alignment for Semi-supervised Medical Image Segmentation—0
Patcher: Patch Transformers with Mixture of Experts for Precise Medical Image SegmentationCode1
Learning Probabilistic Topological Representations Using Discrete Morse Theory—0
A Deep-Learning Usability Expansion Model of Ocean Observations—0
Metrics reloaded: Recommendations for image analysis validationCode1
Incremental Learning Meets Transfer Learning: Application to Multi-site Prostate MRI Segmentation—0
Adaptive Adversarial Training to Improve Adversarial Robustness of DNNs for Medical Image Segmentation and Detection—0
MaxStyle: Adversarial Style Composition for Robust Medical Image SegmentationCode1
Robustness Evaluation and Adversarial Training of an Instance Segmentation Model—0
What Are Expected Queries in End-to-End Object Detection?Code2
H-EMD: A Hierarchical Earth Mover's Distance Method for Instance Segmentation—0
A Dual-fusion Semantic Segmentation Framework With GAN For SAR Images—0
A Bhattacharyya Coefficient-Based Framework for Noise Model-Aware Random Walker Image Segmentation—0
Box2Mask: Weakly Supervised 3D Semantic Instance Segmentation Using Bounding Boxes—0
Suggestive Annotation of Brain MR Images with Gradient-guided Sampling—0
VL-BEiT: Generative Vision-Language Pretraining—0
Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives—0
Siamese Image Modeling for Self-Supervised Vision Representation LearningCode1
Pruning-as-Search: Efficient Neural Architecture Search via Channel Pruning and Structural ReparameterizationCode1
MISSU: 3D Medical Image Segmentation via Self-distilling TransUNetCode1
2D Amodal Instance Segmentation Guided by 3D Shape Prior—0
Multilingual Image Corpus – Towards a Multimodal and Multilingual Dataset—0
The Fully Convolutional Transformer for Medical Image SegmentationCode1
Labeling Where Adapting Fails: Cross-Domain Semantic Segmentation with Point Supervision via Active Selection—0
Amodal Cityscapes: A New Dataset, its Generation, and an Amodal Semantic Segmentation Challenge BaselineCode1
Differentiable Soft-Masked AttentionCode1
Efficient Self-supervised Vision Pretraining with Local Masked ReconstructionCode1
Dynamic Linear Transformer for 3D Biomedical Image SegmentationCode0
Deep learning with RGB and thermal images onboard a drone for monitoring operations—0
Co-Training for Unsupervised Domain Adaptation of Semantic Segmentation ModelsCode0
DeepDefacer: Automatic Removal of Facial Features via U-Net Image Segmentation—0
iFS-RCNN: An Incremental Few-shot Instance SegmenterCode0
D^2NeRF: Self-Supervised Decoupling of Dynamic and Static Objects from a Monocular Video—0
Memory-efficient Segmentation of High-resolution Volumetric MicroCT ImagesCode0
Two-Dimensional Quantum Material Identification via Self-Attention and Soft-labeling in Deep Learning—0
Progressive Multi-scale Consistent Network for Multi-class Fundus Lesion SegmentationCode1
Segmentation Consistency Training: Out-of-Distribution Generalization for Medical Image SegmentationCode0
MVMO: A Multi-Object Dataset for Wide Baseline Multi-View Semantic Segmentation—0
Self-Supervised Pre-training of Vision Transformers for Dense Prediction Tasks—0
Self-Supervised Visual Representation Learning with Semantic GroupingCode1
Pooling Revisited: Your Receptive Field is Suboptimal—0
Few-Shot Adaptation of Pre-Trained Networks for Domain ShiftCode0
You Only Need 90K Parameters to Adapt Light: A Light Weight Transformer for Image Enhancement and Exposure CorrectionCode2
Mean Field inference of CRFs based on GAT—0
Masked Distillation with Receptive TokensCode1
EfficientViT: Multi-Scale Linear Attention for High-Resolution Dense PredictionCode4
Granular Generalized Variable Precision Rough Sets and Rational Approximations—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
4M3I Pre-training (InternImage-H)Validation mIoU62.9—Unverified
5InternImage-HValidation 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