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Semantic Segmentation

Papers

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Showing 5801–5850 of 14763 papers

TitleStatusHype
ISLE: A Framework for Image Level Semantic Segmentation EnsembleCode0
Exploring Weakly Supervised Semantic Segmentation Ensembles for Medical Imaging SystemsCode0
SILOP: An Automated Framework for Semantic Segmentation Using Image Labels Based on Object PerimetersCode0
Class-level Multiple Distributions Representation are Necessary for Semantic Segmentation—0
USAGE: A Unified Seed Area Generation Paradigm for Weakly Supervised Semantic Segmentation—0
MobileVOS: Real-Time Video Object Segmentation Contrastive Learning meets Knowledge Distillation—0
Pixel-wise Gradient Uncertainty for Convolutional Neural Networks applied to Out-of-Distribution SegmentationCode0
Three Guidelines You Should Know for Universally Slimmable Self-Supervised LearningCode1
Mirror U-Net: Marrying Multimodal Fission with Multi-task Learning for Semantic Segmentation in Medical Imaging—0
Modality-Agnostic Debiasing for Single Domain Generalization—0
SCPNet: Semantic Scene Completion on Point CloudCode1
OSIS: Efficient One-stage Network for 3D Instance Segmentation—0
MP-Former: Mask-Piloted Transformer for Image SegmentationCode1
Efficient Semantic Segmentation by Altering Resolutions for Compressed VideosCode1
CrossFormer++: A Versatile Vision Transformer Hinging on Cross-scale AttentionCode2
Amodal Intra-class Instance Segmentation: Synthetic Datasets and BenchmarkCode1
Spatial Correspondence between Graph Neural Network-Segmented Images—0
Universal Instance Perception as Object Discovery and RetrievalCode3
Towards Universal Vision-language Omni-supervised Segmentation—0
Semantics-Aware Dynamic Localization and Refinement for Referring Image Segmentation—0
Probing neural representations of scene perception in a hippocampally dependent task using artificial neural networks—0
Token Sparsification for Faster Medical Image SegmentationCode0
Generalized 3D Self-supervised Learning Framework via Prompted Foreground-Aware Feature Contrast—0
Joint ANN-SNN Co-training for Object Localization and Image Segmentation—0
SemARFlow: Injecting Semantics into Unsupervised Optical Flow Estimation for Autonomous DrivingCode1
Score-Based Generative Models for Medical Image Segmentation using Signed Distance Functions—0
Scaling Up 3D Kernels with Bayesian Frequency Re-parameterization for Medical Image SegmentationCode1
Self-Supervised One-Shot Learning for Automatic Segmentation of StyleGAN ImagesCode0
Combining visibility analysis and deep learning for refinement of semantic 3D building models by conflict classification—0
Iterative Few-shot Semantic Segmentation from Image Label TextCode1
Importance of Aligning Training Strategy with Evaluation for Diffusion Models in 3D Multiclass SegmentationCode1
DACov: A Deeper Analysis of Data Augmentation on the Computed Tomography Segmentation ProblemCode0
Estimating friction coefficient using generative modelling—0
Explainable Semantic Medical Image Segmentation with Style—0
Dynamic Y-KD: A Hybrid Approach to Continual Instance Segmentation—0
Stock Trend Prediction: A Semantic Segmentation Approach—0
Open-world Instance Segmentation: Top-down Learning with Bottom-up Supervision—0
Retinal Image Segmentation with Small Datasets—0
MaskDiff: Modeling Mask Distribution with Diffusion Probabilistic Model for Few-Shot Instance SegmentationCode0
Hybrid Dual Mean-Teacher Network With Double-Uncertainty Guidance for Semi-Supervised Segmentation of MRI ScansCode0
CFR-ICL: Cascade-Forward Refinement with Iterative Click Loss for Interactive Image SegmentationCode0
Contrastive Model Adaptation for Cross-Condition Robustness in Semantic SegmentationCode1
InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data PruningCode2
FCN+: Global Receptive Convolution Makes FCN Great Again—0
DANet: Density Adaptive Convolutional Network with Interactive Attention for 3D Point Clouds—0
A Threefold Review on Deep Semantic Segmentation: Efficiency-oriented, Temporal and Depth-aware design—0
ElC-OIS: Ellipsoidal Clustering for Open-World Instance Segmentation on LiDAR DataCode1
Centroid-centered Modeling for Efficient Vision Transformer Pre-trainingCode0
CLIP-FO3D: Learning Free Open-world 3D Scene Representations from 2D Dense CLIP—0
Full Point Encoding for Local Feature Aggregation in 3D Point Clouds—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