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Semantic Segmentation

Papers

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Showing 6801–6825 of 14763 papers

TitleStatusHype
Discrete-Continuous ADMM for Transductive Inference in Higher-Order MRFs—0
Discovery of Visual Semantics by Unsupervised and Self-Supervised Representation Learning—0
Discover the Mysteries of the Maya: Selected Contributions from the Machine Learning Challenge & The Discovery Challenge Workshop at ECML PKDD 2021—0
Boosting Medical Image Classification with Segmentation Foundation Model—0
An Automatic Seeded Region Growing for 2D Biomedical Image Segmentation—0
3rd Place Solution for MeViS Track in CVPR 2024 PVUW workshop: Motion Expression guided Video Segmentation—0
2DDATA: 2D Detection Annotations Transmittable Aggregation for Semantic Segmentation on Point Cloud—0
Discovering Latent Classes for Semi-Supervised Semantic Segmentation—0
Boosting Mask R-CNN Performance for Long, Thin Forensic Traces with Pre-Segmentation and IoU Region Merging—0
Discover, Hallucinate, and Adapt: Open Compound Domain Adaptation for Semantic Segmentation—0
Boosting Low-Data Instance Segmentation by Unsupervised Pre-training with Saliency Prompt—0
DISCOMAN: Dataset of Indoor SCenes for Odometry, Mapping And Navigation—0
DISCO: Distributed Inference with Sparse Communications—0
Boosting Image Outpainting with Semantic Layout Prediction—0
Boosting Few-shot Semantic Segmentation with Transformers—0
Disaggregation of SMAP L3 Brightness Temperatures to 9km using Kernel Machines—0
Boosting Few-Shot Semantic Segmentation Via Segment Anything Model—0
Direct White Matter Bundle Segmentation using Stacked U-Nets—0
Boosting Cross-spectral Unsupervised Domain Adaptation for Thermal Semantic Segmentation—0
Direct Estimation of Appearance Models for Segmentation—0
Atomic number estimation of dual energy cargo radiographs using a semiempirical transparency model—0
Boosting Box-supervised Instance Segmentation with Pseudo Depth—0
An Automated Real-Time Approach for Image Processing and Segmentation of Fluoroscopic Images and Videos Using a Single Deep Learning Network—0
DINOv2-powered Few-Shot Semantic Segmentation: A Unified Framework via Cross-Model Distillation and 4D Correlation Mining—0
Boosted Training of Convolutional Neural Networks for Multi-Class Segmentation—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