SOTAVerified

Semantic Segmentation

Papers

Showing 56515675 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 Annotations0
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 Segmentation0
Imbalance Knowledge-Driven Multi-modal Network for Land-Cover Semantic Segmentation Using Images and LiDAR Point Clouds0
LinK: Linear Kernel for LiDAR-based 3D PerceptionCode1
Few-Shot 3D Point Cloud Semantic Segmentation via Stratified Class-Specific Attention Based Transformer Network0
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 Learning0
Mask-Free Video Instance SegmentationCode2
MS-MT: Multi-Scale Mean Teacher with Contrastive Unpaired Translation for Cross-Modality Vestibular Schwannoma and Cochlea Segmentation0
OpenInst: A Simple Query-Based Method for Open-World Instance Segmentation0
That Label's Got Style: Handling Label Style Bias for Uncertain Image Segmentation0
Real-Time Semantic Segmentation using Hyperspectral Images for Mapping Unstructured and Unknown EnvironmentsCode1
Learning Expressive Prompting With Residuals for Vision Transformers0
Learning to Zoom and Unzoom0
Leveraging Hidden Positives for Unsupervised Semantic SegmentationCode1
EFEM: Equivariant Neural Field Expectation Maximization for 3D Object Segmentation Without Scene Supervision0
Hi4D: 4D Instance Segmentation of Close Human InteractionCode1
The Devil is in the Points: Weakly Semi-Supervised Instance Segmentation via Point-Guided Mask RepresentationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1InternImage-H (M3I Pre-training)Params (M)1,310Unverified
2ViT-P (InternImage-H)Validation mIoU63.6Unverified
3ONE-PEACEValidation mIoU63Unverified
4M3I Pre-training (InternImage-H)Validation mIoU62.9Unverified
5InternImage-HValidation mIoU62.9Unverified
6BEiT-3Validation mIoU62.8Unverified
7EVAValidation mIoU62.3Unverified
8ViT-P (OneFormer, InternImage-H)Validation mIoU61.6Unverified
9ViT-Adapter-L (Mask2Former, BEiTv2 pretrain)Validation mIoU61.5Unverified
10FD-SwinV2-GValidation mIoU61.4Unverified