SOTAVerified

Semantic Segmentation

Papers

Showing 251275 of 14763 papers

TitleStatusHype
ECA-Net: Efficient Channel Attention for Deep Convolutional Neural NetworksCode2
HiMTok: Learning Hierarchical Mask Tokens for Image Segmentation with Large Multimodal ModelCode2
DSNet: A Novel Way to Use Atrous Convolutions in Semantic SegmentationCode2
HorNet: Efficient High-Order Spatial Interactions with Recursive Gated ConvolutionsCode2
Ambiguous Medical Image Segmentation using Diffusion ModelsCode2
DuPL: Dual Student with Trustworthy Progressive Learning for Robust Weakly Supervised Semantic SegmentationCode2
DreamColour: Controllable Video Colour Editing without TrainingCode2
Domain Adaptive and Generalizable Network Architectures and Training Strategies for Semantic Image SegmentationCode2
DreamLIP: Language-Image Pre-training with Long CaptionsCode2
Dynamic in Static: Hybrid Visual Correspondence for Self-Supervised Video Object SegmentationCode2
AllWeatherNet:Unified Image Enhancement for Autonomous Driving under Adverse Weather and Lowlight-conditionsCode2
Diving into Underwater: Segment Anything Model Guided Underwater Salient Instance Segmentation and A Large-scale DatasetCode2
Does Image Anonymization Impact Computer Vision Training?Code2
MobileOne: An Improved One millisecond Mobile BackboneCode2
AllSpark: Reborn Labeled Features from Unlabeled in Transformer for Semi-Supervised Semantic SegmentationCode2
Diversified and Personalized Multi-rater Medical Image SegmentationCode2
Domain Adaptation with a Single Vision-Language EmbeddingCode2
Dynamic Tuning Towards Parameter and Inference Efficiency for ViT AdaptationCode2
UNetFormer: A UNet-like Transformer for Efficient Semantic Segmentation of Remote Sensing Urban Scene ImageryCode2
Hybrid-Segmentor: A Hybrid Approach to Automated Fine-Grained Crack Segmentation in Civil InfrastructureCode2
Digital Twin Generation from Visual Data: A SurveyCode2
Dilated Neighborhood Attention TransformerCode2
Diffuse, Attend, and Segment: Unsupervised Zero-Shot Segmentation using Stable DiffusionCode2
DiffRect: Latent Diffusion Label Rectification for Semi-supervised Medical Image SegmentationCode2
Diffusion models as plug-and-play priorsCode2
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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