SOTAVerified

Semantic Segmentation

Papers

Showing 476500 of 14763 papers

TitleStatusHype
Diffusion models as plug-and-play priorsCode2
Panoptic NeRF: 3D-to-2D Label Transfer for Panoptic Urban Scene SegmentationCode2
Panoptic nuScenes: A Large-Scale Benchmark for LiDAR Panoptic Segmentation and TrackingCode2
DytanVO: Joint Refinement of Visual Odometry and Motion Segmentation in Dynamic EnvironmentsCode2
DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous ConvolutionCode2
Per-Pixel Classification is Not All You Need for Semantic SegmentationCode2
Densely Connected Parameter-Efficient Tuning for Referring Image SegmentationCode2
Atlas: End-to-End 3D Scene Reconstruction from Posed ImagesCode2
DenseNets Reloaded: Paradigm Shift Beyond ResNets and ViTsCode2
Delineate Anything: Resolution-Agnostic Field Boundary Delineation on Satellite ImageryCode2
Adaptive Bidirectional Displacement for Semi-Supervised Medical Image SegmentationCode2
Deep Video Prior for Video Consistency and PropagationCode2
Delivering Arbitrary-Modal Semantic SegmentationCode2
3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image SegmentationCode2
Prompt Pre-Training with Twenty-Thousand Classes for Open-Vocabulary Visual RecognitionCode2
A Tale of Two Features: Stable Diffusion Complements DINO for Zero-Shot Semantic CorrespondenceCode2
Advancing Plain Vision Transformer Towards Remote Sensing Foundation ModelCode2
Deep Spectral Methods: A Surprisingly Strong Baseline for Unsupervised Semantic Segmentation and LocalizationCode2
DFormer: Rethinking RGBD Representation Learning for Semantic SegmentationCode2
Understanding the Tricks of Deep Learning in Medical Image Segmentation: Challenges and Future DirectionsCode2
Deep Hierarchical Semantic SegmentationCode2
ASAM: Boosting Segment Anything Model with Adversarial TuningCode2
Recent Advances in Medical Imaging Segmentation: A SurveyCode2
C2AM: Contrastive Learning of Class-Agnostic Activation Map for Weakly Supervised Object Localization and Semantic SegmentationCode2
Deep Incubation: Training Large Models by Divide-and-ConqueringCode2
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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