SOTAVerified

Semantic Segmentation

Papers

Showing 551600 of 14763 papers

TitleStatusHype
CLIP is Also an Efficient Segmenter: A Text-Driven Approach for Weakly Supervised Semantic SegmentationCode2
Deep Incubation: Training Large Models by Divide-and-ConqueringCode2
UNETR++: Delving into Efficient and Accurate 3D Medical Image SegmentationCode2
ZegCLIP: Towards Adapting CLIP for Zero-shot Semantic SegmentationCode2
MIC: Masked Image Consistency for Context-Enhanced Domain AdaptationCode2
PLA: Language-Driven Open-Vocabulary 3D Scene UnderstandingCode2
Semi-Supervised Confidence-Level-based Contrastive Discrimination for Class-Imbalanced Semantic SegmentationCode2
OpenScene: 3D Scene Understanding with Open VocabulariesCode2
Medical Image Segmentation Review: The success of U-NetCode2
CDDFuse: Correlation-Driven Dual-Branch Feature Decomposition for Multi-Modality Image FusionCode2
Fast-iTPN: Integrally Pre-Trained Transformer Pyramid Network with Token MigrationCode2
MogaNet: Multi-order Gated Aggregation NetworkCode2
SimpleClick: Interactive Image Segmentation with Simple Vision TransformersCode2
Decoupling Features in Hierarchical Propagation for Video Object SegmentationCode2
Model-Based Imitation Learning for Urban DrivingCode2
SegViT: Semantic Segmentation with Plain Vision TransformersCode2
The Equalization Losses: Gradient-Driven Training for Long-tailed Object RecognitionCode2
Point Transformer V2: Grouped Vector Attention and Partition-based PoolingCode2
What the DAAM: Interpreting Stable Diffusion Using Cross AttentionCode2
Open-Vocabulary Semantic Segmentation with Mask-adapted CLIPCode2
Mask3D: Mask Transformer for 3D Semantic Instance SegmentationCode2
GMMSeg: Gaussian Mixture based Generative Semantic Segmentation ModelsCode2
MobileViTv3: Mobile-Friendly Vision Transformer with Simple and Effective Fusion of Local, Global and Input FeaturesCode2
3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image SegmentationCode2
Dilated Neighborhood Attention TransformerCode2
Generalized Parametric Contrastive LearningCode2
Understanding the Tricks of Deep Learning in Medical Image Segmentation: Challenges and Future DirectionsCode2
SegNeXt: Rethinking Convolutional Attention Design for Semantic SegmentationCode2
DytanVO: Joint Refinement of Visual Odometry and Motion Segmentation in Dynamic EnvironmentsCode2
Scalable SoftGroup for 3D Instance Segmentation on Point CloudsCode2
MCIBI++: Soft Mining Contextual Information Beyond Image for Semantic SegmentationCode2
Revisiting Weak-to-Strong Consistency in Semi-Supervised Semantic SegmentationCode2
PyMIC: A deep learning toolkit for annotation-efficient medical image segmentationCode2
FEC: Fast Euclidean Clustering for Point Cloud SegmentationCode2
Advancing Plain Vision Transformer Towards Remote Sensing Foundation ModelCode2
Occlusion-Aware Instance Segmentation via BiLayer Network ArchitecturesCode2
MinVIS: A Minimal Video Instance Segmentation Framework without Video-based TrainingCode2
HorNet: Efficient High-Order Spatial Interactions with Recursive Gated ConvolutionsCode2
In Defense of Online Models for Video Instance SegmentationCode2
SatMAE: Pre-training Transformers for Temporal and Multi-Spectral Satellite ImageryCode2
Wave-ViT: Unifying Wavelet and Transformers for Visual Representation LearningCode2
SFNet: Faster, Accurate, and Domain Agnostic Semantic Segmentation via Semantic FlowCode2
2DPASS: 2D Priors Assisted Semantic Segmentation on LiDAR Point CloudsCode2
More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using SparsityCode2
CoBEVT: Cooperative Bird's Eye View Semantic Segmentation with Sparse TransformersCode2
Efficient Spatial-Temporal Information Fusion for LiDAR-Based 3D Moving Object SegmentationCode2
Improving Nighttime Driving-Scene Segmentation via Dual Image-adaptive Learnable FiltersCode2
Rethinking Unsupervised Domain Adaptation for Semantic SegmentationCode2
LaserMix for Semi-Supervised LiDAR Semantic SegmentationCode2
LViT: Language meets Vision Transformer in Medical Image SegmentationCode2
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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