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Semantic Segmentation

Papers

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Showing 7301–7350 of 14763 papers

TitleStatusHype
Label-Efficient LiDAR Panoptic Segmentation—0
Label-efficient Hybrid-supervised Learning for Medical Image Segmentation—0
Label-Driven Reconstruction for Domain Adaptation in Semantic Segmentation—0
Label Calibration for Semantic Segmentation Under Domain Shift—0
Label Assistant: A Workflow for Assisted Data Annotation in Image Segmentation Tasks—0
Bayesian image segmentations by Potts prior and loopy belief propagation—0
L^3U-net: Low-Latency Lightweight U-net Based Image Segmentation Model for Parallel CNN Processors—0
L2T-DLN: Learning to Teach with Dynamic Loss Network—0
Deeply supervised UNet for semantic segmentation to assist dermatopathological assessment of Basal Cell Carcinoma (BCC)—0
Kullback-Leibler Divergence-Based Fuzzy C-Means Clustering Incorporating Morphological Reconstruction and Wavelet Frames for Image Segmentation—0
K-textures, a self-supervised hard clustering deep learning algorithm for satellite image segmentation—0
Deeply Self-Supervised Contour Embedded Neural Network Applied to Liver Segmentation—0
Bayesian Generative Models for Knowledge Transfer in MRI Semantic Segmentation Problems—0
Bayesian Federated Neural Matching that Completes Full Information—0
Deeply Learning the Messages in Message Passing Inference—0
Deeply Cascaded U-Net for Multi-Task Image Processing—0
Bayesian Deep Learning for Affordance Segmentation in images—0
Deep LOGISMOS: Deep Learning Graph-based 3D Segmentation of Pancreatic Tumors on CT scans—0
Koopman-based spectral clustering of directed and time-evolving graphs—0
Kolmogorov-Arnold Network for Remote Sensing Image Semantic Segmentation—0
Deep LF-Net: Semantic Lung Segmentation from Indian Chest Radiographs Including Severely Unhealthy Images—0
Layered Logic Classifiers: Exploring the `And' and `Or' Relations—0
Bayesian Deep Learning Approaches for Uncertainty-Aware Retinal OCT Image Segmentation for Multiple Sclerosis—0
Layer Ensembles: A Single-Pass Uncertainty Estimation in Deep Learning for Segmentation—0
Layout Aware Inpainting for Automated Furniture Removal in Indoor Scenes—0
Ammonia-Net: A Multi-task Joint Learning Model for Multi-class Segmentation and Classification in Tooth-marked Tongue Diagnosis—0
Know What Your Neighbors Do: 3D Semantic Segmentation of Point Clouds—0
Know "No'' Better: A Data-Driven Approach for Enhancing Negation Awareness in CLIP—0
Deep learning with RGB and thermal images onboard a drone for monitoring operations—0
Knowledge distillation with Segment Anything (SAM) model for Planetary Geological Mapping—0
Deep Learning with Anatomical Priors: Imitating Enhanced Autoencoders in Latent Space for Improved Pelvic Bone Segmentation in MRI—0
Knowledge Distillation in Vision Transformers: A Critical Review—0
Knowledge distillation from multi-modal to mono-modal segmentation networks—0
Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment—0
Deep Learning Training Procedure Augmentations—0
Leaf Segmentation and Counting with Deep Learning: on Model Certainty, Test-Time Augmentation, Trade-Offs—0
LeanConvNets: Low-cost Yet Effective Convolutional Neural Networks—0
LeAP: Consistent multi-domain 3D labeling using Foundation Models—0
Bayesian Active Contours with Affine-Invariant, Elastic Shape Prior—0
AMLP:Adaptive Masking Lesion Patches for Self-supervised Medical Image Segmentation—0
Actor and Action Modular Network for Text-based Video Segmentation—0
Actor-Action Semantic Segmentation with Grouping Process Models—0
Pseudo-Label Quality Decoupling and Correction for Semi-Supervised Instance Segmentation—0
Rethinking the Mean Teacher Strategy from the Perspective of Self-paced Learning—0
Region homogeneity in the Logarithmic Image Processing framework: application to region growing algorithms—0
Guided Anisotropic Diffusion and Iterative Learning for Weakly Supervised Change Detection—0
Deep Learning Techniques for Video Instance Segmentation: A Survey—0
Knowledge Distillation for Incremental Learning in Semantic Segmentation—0
BayeSeg: Bayesian Modeling for Medical Image Segmentation with Interpretable Generalizability—0
Knowledge Distillation Circumvents Nonlinearity for Optical Convolutional Neural Networks—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