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Semantic Segmentation

Papers

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Showing 76–100 of 14763 papers

TitleStatusHype
LVPNet: A Latent-variable-based Prediction-driven End-to-end Framework for Lossless Compression of Medical ImagesCode0
TextBraTS: Text-Guided Volumetric Brain Tumor Segmentation with Innovative Dataset Development and Fusion Module ExplorationCode1
Automated MRI Tumor Segmentation using hybrid U-Net with Transformer and Efficient Attention—0
Pixel-wise Modulated Dice Loss for Medical Image Segmentation—0
Scaling-Up the Pretraining of the Earth Observation Foundation Model PhilEO to the MajorTOM DatasetCode0
KDMOS:Knowledge Distillation for Motion SegmentationCode0
Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment—0
DepthSeg: Depth prompting in remote sensing semantic segmentation—0
Image Segmentation with Large Language Models: A Survey with Perspectives for Intelligent Transportation Systems—0
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy—0
A Comprehensive Survey on Video Scene Parsing:Advances, Challenges, and Prospects—0
Simple is what you need for efficient and accurate medical image segmentationCode0
MorphSAM: Learning the Morphological Prompts from Atlases for Spine Image Segmentation—0
HierVL: Semi-Supervised Segmentation leveraging Hierarchical Vision-Language Synergy with Dynamic Text-Spatial Query Alignment—0
Open-Set LiDAR Panoptic Segmentation Guided by Uncertainty-Aware Learning—0
Combining Self-attention and Dilation Convolutional for Semantic Segmentation of Coal Maceral Groups—0
A large-scale, physically-based synthetic dataset for satellite pose estimation—0
M^3-VOS: Multi-Phase, Multi-Transition, and Multi-Scenery Video Object SegmentationCode1
MRI-CORE: A Foundation Model for Magnetic Resonance Imaging—0
Prohibited Items Segmentation via Occlusion-aware Bilayer ModelingCode0
SWDL: Stratum-Wise Difference Learning with Deep Laplacian Pyramid for Semi-Supervised 3D Intracranial Hemorrhage SegmentationCode0
Med-URWKV: Pure RWKV With ImageNet Pre-training For Medical Image Segmentation—0
Demonstrating Multi-Suction Item Picking at Scale via Multi-Modal Learning of Pick Success—0
Semantic Localization Guiding Segment Anything Model For Reference Remote Sensing Image Segmentation—0
ConStyX: Content Style Augmentation for Generalizable Medical Image SegmentationCode0
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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