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Semantic Segmentation

Papers

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Showing 4151–4200 of 14763 papers

TitleStatusHype
Whole-brain radiomics for clustered federated personalization in brain tumor segmentationCode0
FusionU-Net: U-Net with Enhanced Skip Connection for Pathology Image SegmentationCode1
Temporal Embeddings: Scalable Self-Supervised Temporal Representation Learning from Spatiotemporal Data for Multimodal Computer Vision—0
IDRNet: Intervention-Driven Relation Network for Semantic SegmentationCode2
Label-efficient Segmentation via Affinity PropagationCode1
NeuroQuantify -- An Image Analysis Software for Detection and Quantification of Neurons and Neurites using Deep LearningCode0
Deep Conditional Shape Models for 3D cardiac image segmentation—0
Evaluation and improvement of Segment Anything Model for interactive histopathology image segmentationCode0
Motion2Language, unsupervised learning of synchronized semantic motion segmentationCode1
On the Transferability of Learning Models for Semantic Segmentation for Remote Sensing DataCode0
SeUNet-Trans: A Simple yet Effective UNet-Transformer Model for Medical Image Segmentation—0
RefConv: Re-parameterized Refocusing Convolution for Powerful ConvNetsCode1
Top-K Pooling with Patch Contrastive Learning for Weakly-Supervised Semantic Segmentation—0
Tabletop Transparent Scene Reconstruction via Epipolar-Guided Optical Flow with Monocular Depth Completion Prior—0
Image Augmentation with Controlled Diffusion for Weakly-Supervised Semantic Segmentation—0
Equirectangular image construction method for standard CNNs for Semantic Segmentation—0
Vision Transformers increase efficiency of 3D cardiac CT multi-label segmentationCode0
Revisiting Multi-modal 3D Semantic Segmentation in Real-world Autonomous Driving—0
Re-initialization-free Level Set Method via Molecular Beam Epitaxy Equation Regularization for Image Segmentation—0
Ultrasound Image Segmentation of Thyroid Nodule via Latent Semantic Feature Co-Registration—0
Learning to Adapt SAM for Segmenting Cross-domain Point Clouds—0
UniParser: Multi-Human Parsing with Unified Correlation Representation LearningCode1
UniPAD: A Universal Pre-training Paradigm for Autonomous DrivingCode2
PonderV2: Pave the Way for 3D Foundation Model with A Universal Pre-training ParadigmCode2
Volumetric Medical Image Segmentation via Scribble Annotations and Shape Priors—0
Unsupervised Learning of Object-Centric Embeddings for Cell Instance Segmentation in Microscopy ImagesCode1
Virtual Augmented Reality for Atari Reinforcement LearningCode0
NSM4D: Neural Scene Model Based Online 4D Point Cloud Sequence Understanding—0
SSG2: A new modelling paradigm for semantic segmentationCode1
BaSAL: Size-Balanced Warm Start Active Learning for LiDAR Semantic SegmentationCode0
GraphAlign: Enhancing Accurate Feature Alignment by Graph matching for Multi-Modal 3D Object Detection—0
Visual Self-supervised Learning Scheme for Dense Prediction Tasks on X-ray Images—0
Line Detection and Segmentation of Annual Crops Using Hybrid MethodCode0
3D TransUNet: Advancing Medical Image Segmentation through Vision TransformersCode4
PointHR: Exploring High-Resolution Architectures for 3D Point Cloud SegmentationCode1
SAM-OCTA: Prompting Segment-Anything for OCTA Image SegmentationCode1
PeP: a Point enhanced Painting method for unified point cloud tasks—0
Robust Unsupervised Domain Adaptation by Retaining Confident Entropy via Edge Concatenation—0
S4C: Self-Supervised Semantic Scene Completion with Neural Fields—0
Relational Prior Knowledge Graphs for Detection and Instance SegmentationCode1
Causal Unsupervised Semantic SegmentationCode1
Context-Enhanced Detector For Building Detection From Remote Sensing Images—0
Heuristic Vision Pre-Training with Self-Supervised and Supervised Multi-Task Learning—0
CLIP for Lightweight Semantic Segmentation—0
Impact of Label Types on Training SWIN Models with Overhead Imagery—0
Distilling Efficient Vision Transformers from CNNs for Semantic Segmentation—0
HaarNet: Large-scale Linear-Morphological Hybrid Network for RGB-D Semantic Segmentation—0
Zero-Shot Open-Vocabulary Tracking with Large Pre-Trained Models—0
Utilizing Synthetic Data for Medical Vision-Language Pre-training: Bypassing the Need for Real ImagesCode0
Self-supervised Object-Centric Learning for Videos—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