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Semantic Segmentation

Papers

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Showing 10851–10900 of 14763 papers

TitleStatusHype
Segment Anything is A Good Pseudo-label Generator for Weakly Supervised Semantic Segmentation—0
Segment Anything Meets Semantic Communication—0
Segment Anything Model Can Not Segment Anything: Assessing AI Foundation Model's Generalizability in Permafrost Mapping—0
Segment Anything Model for automated image data annotation: empirical studies using text prompts from Grounding DINO—0
Segment Anything Model for Brain Tumor Segmentation—0
Segment Anything Model Meets Image Harmonization—0
Segment Anything Model (SAM) for Digital Pathology: Assess Zero-shot Segmentation on Whole Slide Imaging—0
Segment Anything Model (SAM) Meets Glass: Mirror and Transparent Objects Cannot Be Easily Detected—0
Enhancing the Reliability of Segment Anything Model for Auto-Prompting Medical Image Segmentation with Uncertainty Rectification—0
SegmentAnyTree: A sensor and platform agnostic deep learning model for tree segmentation using laser scanning data—0
Segmentation and Restoration of Images on Surfaces by Parametric Active Contours with Topology Changes—0
Segmentation-by-Detection: A Cascade Network for Volumetric Medical Image Segmentation—0
Segmentation by Factorization: Unsupervised Semantic Segmentation for Pathology by Factorizing Foundation Model Features—0
Segmentation-free Direct Iris Localization Networks—0
Segmentation Guided Attention Networks for Visual Question Answering—0
Segmentation Guided Sparse Transformer for Under-Display Camera Image Restoration—0
Segmentation hiérarchique faiblement supervisée—0
Segmentation Network with Compound Loss Function for Hydatidiform Mole Hydrops Lesion Recognition—0
Segmentation of 3D Dental Images Using Deep Learning—0
Segmentation of Cellular Patterns in Confocal Images of Melanocytic Lesions in vivo via a Multiscale Encoder-Decoder Network (MED-Net)—0
Segmentation of Drone Collision Hazards in Airborne RADAR Point Clouds Using PointNet—0
MAF-Net: Multiple attention-guided fusion network for fundus vascular image segmentation—0
Segmentation of kidney stones in endoscopic video feeds—0
Segmentation of Kidney Tumors on Non-Contrast CT Images using Protuberance Detection Network—0
Segmentation of Knee Bones for Osteoarthritis Assessment: A Comparative Analysis of Supervised, Few-Shot, and Zero-Shot Learning Approaches—0
Segmentation of large images based on super-pixels and community detection in graphs—0
Segmentation of Microscopy Data for finding Nuclei in Divergent Images—0
Segmentation of Multiple Myeloma Plasma Cells in Microscopy Images with Noisy Labels—0
Segmentation of Satellite Imagery using U-Net Models for Land Cover Classification—0
Segmentation of skin lesions and their attributes using Generative Adversarial Networks—0
Segmentation of Surgical Instruments for Minimally-Invasive Robot-Assisted Procedures Using Generative Deep Neural Networks—0
Segmentation of the cortical plate in fetal brain MRI with a topological loss—0
Segmentation of the veterinary cytological images for fast neoplastic tumors diagnosis—0
Segmentation of VHR EO Images using Unsupervised Learning—0
Segmentation of waterbodies in remote sensing images using deep stacked ensemble model—0
Segmentation overlapping wear particles with few labelled data and imbalance sample—0
Segmentation Quality and Volumetric Accuracy in Medical Imaging—0
Segmentation Re-thinking Uncertainty Estimation Metrics for Semantic Segmentation—0
Segment Based 3D Object Shape Priors—0
Segment Beyond View: Handling Partially Missing Modality for Audio-Visual Semantic Segmentation—0
Segment Concealed Objects with Incomplete Supervision—0
Segment Every Reference Object in Spatial and Temporal Spaces—0
Cooperative Semantic Segmentation and Image Restoration in Adverse Environmental Conditions—0
Segment-Fusion: Hierarchical Context Fusion for Robust 3D Semantic Segmentation—0
Language-Level Semantics Conditioned 3D Point Cloud Segmentation—0
Segmenting across places: The need for fair transfer learning with satellite imagery—0
Segmenting Dead Sea Scroll Fragments for a Scientific Image Set—0
Segmenting Fetal Head with Efficient Fine-tuning Strategies in Low-resource Settings: an empirical study with U-Net—0
Segmenting objects with Bayesian fusion of active contour models and convnet priors—0
Segmenting Ships in Satellite Imagery With Squeeze and Excitation U-Net—0
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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