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Semantic Segmentation

Papers

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Showing 5651–5700 of 14763 papers

TitleStatusHype
Multi-scale Hierarchical Vision Transformer with Cascaded Attention Decoding for Medical Image SegmentationCode1
Self-positioning Point-based Transformer for Point Cloud UnderstandingCode1
Towards Foundation Models and Few-Shot Parameter-Efficient Fine-Tuning for Volumetric Organ SegmentationCode1
Mask-free OVIS: Open-Vocabulary Instance Segmentation without Manual Mask Annotations—0
SC-VAE: Sparse Coding-based Variational Autoencoder with Learned ISTACode0
Time Series Segmentation Applied to a New Data Set for Mobile Sensing of Human ActivitiesCode1
Spatiotemporal Self-supervised Learning for Point Clouds in the WildCode1
FMAS: Fast Multi-Objective SuperNet Architecture Search for Semantic Segmentation—0
Imbalance Knowledge-Driven Multi-modal Network for Land-Cover Semantic Segmentation Using Images and LiDAR Point Clouds—0
LinK: Linear Kernel for LiDAR-based 3D PerceptionCode1
Few-Shot 3D Point Cloud Semantic Segmentation via Stratified Class-Specific Attention Based Transformer Network—0
Explicit Attention-Enhanced Fusion for RGB-Thermal Perception TasksCode1
AutoKary2022: A Large-Scale Densely Annotated Dataset for Chromosome Instance SegmentationCode0
Medical Image Analysis using Deep Relational Learning—0
Mask-Free Video Instance SegmentationCode2
MS-MT: Multi-Scale Mean Teacher with Contrastive Unpaired Translation for Cross-Modality Vestibular Schwannoma and Cochlea Segmentation—0
OpenInst: A Simple Query-Based Method for Open-World Instance Segmentation—0
That Label's Got Style: Handling Label Style Bias for Uncertain Image Segmentation—0
Real-Time Semantic Segmentation using Hyperspectral Images for Mapping Unstructured and Unknown EnvironmentsCode1
Learning Expressive Prompting With Residuals for Vision Transformers—0
Learning to Zoom and Unzoom—0
Leveraging Hidden Positives for Unsupervised Semantic SegmentationCode1
EFEM: Equivariant Neural Field Expectation Maximization for 3D Object Segmentation Without Scene Supervision—0
Hi4D: 4D Instance Segmentation of Close Human InteractionCode1
The Devil is in the Points: Weakly Semi-Supervised Instance Segmentation via Point-Guided Mask RepresentationCode1
Vision Transformer with Quadrangle AttentionCode2
Universal Few-shot Learning of Dense Prediction Tasks with Visual Token MatchingCode2
You Only Need One Thing One Click: Self-Training for Weakly Supervised 3D Scene UnderstandingCode1
You Only Segment Once: Towards Real-Time Panoptic SegmentationCode2
VisDA 2022 Challenge: Domain Adaptation for Industrial Waste SortingCode1
BoxVIS: Video Instance Segmentation with Box AnnotationsCode1
A Contrastive Learning Scheme with Transformer Innate PatchesCode0
Hierarchical Dense Correlation Distillation for Few-Shot SegmentationCode1
Active Finetuning: Exploiting Annotation Budget in the Pretraining-Finetuning ParadigmCode1
Both Style and Distortion Matter: Dual-Path Unsupervised Domain Adaptation for Panoramic Semantic Segmentation—0
Instant Domain Augmentation for LiDAR Semantic Segmentation—0
Reliability-Hierarchical Memory Network for Scribble-Supervised Video Object SegmentationCode1
MDQE: Mining Discriminative Query Embeddings to Segment Occluded Instances on Challenging VideosCode1
Spatio-Temporal driven Attention Graph Neural Network with Block Adjacency matrix (STAG-NN-BA)—0
ViPFormer: Efficient Vision-and-Pointcloud Transformer for Unsupervised Pointcloud UnderstandingCode1
MultiTalent: A Multi-Dataset Approach to Medical Image SegmentationCode1
UnScene3D: Unsupervised 3D Instance Segmentation for Indoor Scenes—0
Spatio-Temporal Pixel-Level Contrastive Learning-based Source-Free Domain Adaptation for Video Semantic SegmentationCode0
SUDS: Scalable Urban Dynamic Scenes—0
OVeNet: Offset Vector Network for Semantic SegmentationCode0
IFSeg: Image-free Semantic Segmentation via Vision-Language ModelCode1
DoNet: Deep De-overlapping Network for Cytology Instance SegmentationCode1
PeakNet: An Autonomous Bragg Peak Finder with Deep Neural Networks—0
Masked Scene Contrast: A Scalable Framework for Unsupervised 3D Representation Learning—0
Principles of Forgetting in Domain-Incremental Semantic Segmentation in Adverse Weather ConditionsCode0
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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