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Semantic Segmentation

Papers

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Showing 1051–1100 of 14763 papers

TitleStatusHype
Tree-NET: Enhancing Medical Image Segmentation Through Efficient Low-Level Feature Training—0
EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation—0
Semantic Segmentation for Sequential Historical Maps by Learning from Only One Map—0
Merging Context Clustering with Visual State Space Models for Medical Image SegmentationCode2
A Multi-task Supervised Compression Model for Split ComputingCode0
Efficient Connectivity-Preserving Instance Segmentation with Supervoxel-Based Loss FunctionCode1
Evidential Calibrated Uncertainty-Guided Interactive Segmentation paradigm for Ultrasound Images—0
Leverage Cross-Attention for End-to-End Open-Vocabulary Panoptic Reconstruction—0
nnY-Net: Swin-NeXt with Cross-Attention for 3D Medical Images Segmentation—0
Understanding Fine-tuning CLIP for Open-vocabulary Semantic Segmentation in Hyperbolic Space—0
Common3D: Self-Supervised Learning of 3D Morphable Models for Common Objects in Neural Feature SpaceCode0
DocSAM: Unified Document Image Segmentation via Query Decomposition and Heterogeneous Mixed Learning—0
Relation3D : Enhancing Relation Modeling for Point Cloud Instance SegmentationCode1
SAM2Object: Consolidating View Consistency via SAM2 for Zero-Shot 3D Instance Segmentation—0
Minimizing Labeled, Maximizing Unlabeled: An Image-Driven Approach for Video Instance Segmentation—0
Take the Bull by the Horns: Learning to Segment Hard SamplesCode0
Mamba4D: Efficient 4D Point Cloud Video Understanding with Disentangled Spatial-Temporal State Space ModelsCode1
DSV-LFS: Unifying LLM-Driven Semantic Cues with Visual Features for Robust Few-Shot Segmentation—0
EntitySAM: Segment Everything in Video—0
Advancing Manga Analysis: Comprehensive Segmentation Annotations for the Manga109 Dataset—0
WISH: Weakly Supervised Instance Segmentation using Heterogeneous Labels—0
EffiDec3D: An Optimized Decoder for High-Performance and Efficient 3D Medical Image SegmentationCode1
Scaling up Image Segmentation across Data and Tasks—0
Prototype-Based Image Prompting for Weakly Supervised Histopathological Image Segmentation—0
Multi-Modal Contrastive Masked Autoencoders: A Two-Stage Progressive Pre-training Approach for RGBD Datasets—0
WISNet: Pseudo Label Generation on Unbalanced and Patch Annotated Waste Images—0
Decoupled Motion Expression Video Segmentation—0
Camouflage Anything: Learning to Hide using Controlled Out-painting and Representation Engineering—0
Annotation Ambiguity Aware Semi-Supervised Medical Image Segmentation—0
Generative Map Priors for Collaborative BEV Semantic Segmentation—0
SemiDAViL: Semi-supervised Domain Adaptation with Vision-Language Guidance for Semantic Segmentation—0
Multi-Label Prototype Visual Spatial Search for Weakly Supervised Semantic Segmentation—0
Weakly Supervised Semantic Segmentation via Progressive Confidence Region ExpansionCode0
Dual Semantic Guidance for Open Vocabulary Semantic Segmentation—0
Keep the Balance: A Parameter-Efficient Symmetrical Framework for RGB+X Semantic Segmentation—0
Mamba-Reg: Vision Mamba Also Needs Registers—0
FFR: Frequency Feature Rectification for Weakly Supervised Semantic SegmentationCode0
The Impact Label Noise and Choice of Threshold has on Cross-Entropy and Soft-Dice in Image Segmentation—0
Universal Domain Adaptation for Semantic SegmentationCode0
Higher-Order Ratio Cycles for Fast and Globally Optimal Shape MatchingCode0
DTOS: Dynamic Time Object Sensing with Large Multimodal ModelCode0
Semantic and Sequential Alignment for Referring Video Object Segmentation—0
Convex Combination Star Shape Prior for Data-driven Image Semantic Segmentation—0
beta-FFT: Nonlinear Interpolation and Differentiated Training Strategies for Semi-Supervised Medical Image Segmentation—0
A Semantic Knowledge Complementarity based Decoupling Framework for Semi-supervised Class-imbalanced Medical Image Segmentation—0
POT: Prototypical Optimal Transport for Weakly Supervised Semantic SegmentationCode1
Perceptual Inductive Bias Is What You Need Before Contrastive Learning—0
CSC-PA: Cross-image Semantic Correlation via Prototype Attentions for Single-network Semi-supervised Breast Tumor SegmentationCode1
UNICL-SAM: Uncertainty-Driven In-Context Segmentation with Part Prototype Discovery—0
Boosting the Dual-Stream Architecture in Ultra-High Resolution Segmentation with Resolution-Biased Uncertainty EstimationCode0
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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