SOTAVerified

Semantic Segmentation

Papers

Showing 95769600 of 14763 papers

TitleStatusHype
Domain Adaptive Semantic Segmentation with Self-Supervised Depth EstimationCode1
Exploring Relational Context for Multi-Task Dense PredictionCode1
A Deep Learning Object Detection Method for an Efficient Clusters Initialization0
Distributional Gaussian Process Layers for Outlier Detection in Image Segmentation0
Two stages for visual object tracking0
Twins: Revisiting the Design of Spatial Attention in Vision TransformersCode1
Point Cloud Learning with Transformer0
Rethinking BiSeNet For Real-time Semantic SegmentationCode1
Semi-Supervised Semantic Segmentation with Pixel-Level Contrastive Learning from a Class-wise Memory BankCode1
Every Annotation Counts: Multi-label Deep Supervision for Medical Image SegmentationCode0
ACDC: The Adverse Conditions Dataset with Correspondences for Robust Semantic Driving Scene Perception0
Analyzing Green View Index and Green View Index best path using Google Street View and deep learningCode0
Vision Transformers with Patch DiversificationCode1
Multimodal Contrastive Training for Visual Representation Learning0
Three-Dimensional Embedded Attentive RNN (3D-EAR) Segmentor for Left Ventricle Delineation from Myocardial Velocity Mapping0
MIDeepSeg: Minimally Interactive Segmentation of Unseen Objects from Medical Images Using Deep LearningCode1
Quantization of Deep Neural Networks for Accurate Edge Computing0
A Novel Transformer Based Semantic Segmentation Scheme for Fine-Resolution Remote Sensing ImagesCode2
Learning to Better Segment Objects from Unseen Classes with Unlabeled Videos0
UnrealROX+: An Improved Tool for Acquiring Synthetic Data from Virtual 3D EnvironmentsCode1
Pri3D: Can 3D Priors Help 2D Representation Learning?Code1
NanoNet: Real-Time Polyp Segmentation in Video Capsule Endoscopy and ColonoscopyCode1
All Tokens Matter: Token Labeling for Training Better Vision TransformersCode1
Semi-Supervised Segmentation of Concrete Aggregate Using Consensus Regularisation and Prior Guidance0
A Data-Adaptive Loss Function for Incomplete Data and Incremental Learning in Semantic Image Segmentation0
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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