SOTAVerified

Semantic Segmentation

Papers

Showing 22012225 of 14763 papers

TitleStatusHype
Applying Conditional Generative Adversarial Networks for Imaging Diagnosis0
Data-driven Verification of DNNs for Object Recognition0
FastSAM-3DSlicer: A 3D-Slicer Extension for 3D Volumetric Segment Anything Model with Uncertainty QuantificationCode1
Latent Diffusion for Medical Image Segmentation: End to end learning for fast sampling and accuracyCode1
ColorMAE: Exploring data-independent masking strategies in Masked AutoEncodersCode0
Weighting Pseudo-Labels via High-Activation Feature Index Similarity and Object Detection for Semi-Supervised SegmentationCode0
Benchmarking Robust Self-Supervised Learning Across Diverse Downstream TasksCode0
Dual-level Adaptive Self-Labeling for Novel Class Discovery in Point Cloud SegmentationCode1
Close the Sim2real Gap via Physically-based Structured Light Synthetic Data Simulation0
Progressive Proxy Anchor Propagation for Unsupervised Semantic SegmentationCode1
ClearCLIP: Decomposing CLIP Representations for Dense Vision-Language Inference0
Serialized Point Mamba: A Serialized Point Cloud Mamba Segmentation Model0
Instance-wise Uncertainty for Class Imbalance in Semantic Segmentation0
Generative AI Driven Task-Oriented Adaptive Semantic Communications0
The Devil is in the Statistics: Mitigating and Exploiting Statistics Difference for Generalizable Semi-supervised Medical Image SegmentationCode1
Leveraging Segment Anything Model in Identifying Buildings within Refugee Camps (SAM4Refugee) from Satellite Imagery for Humanitarian OperationsCode0
LoRA-PT: Low-Rank Adapting UNETR for Hippocampus Segmentation Using Principal Tensor Singular Values and VectorsCode0
Crowd-SAM: SAM as a Smart Annotator for Object Detection in Crowded ScenesCode2
TCFormer: Visual Recognition via Token Clustering TransformerCode3
FoodMem: Near Real-time and Precise Food Video Segmentation0
Mitigating Background Shift in Class-Incremental Semantic SegmentationCode1
OAM-TCD: A globally diverse dataset of high-resolution tree cover mapsCode1
Centering the Value of Every Modality: Towards Efficient and Resilient Modality-agnostic Semantic Segmentation0
Learning Modality-agnostic Representation for Semantic Segmentation from Any Modalities0
SGIFormer: Semantic-guided and Geometric-enhanced Interleaving Transformer for 3D Instance SegmentationCode1
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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
4InternImage-HValidation mIoU62.9Unverified
5M3I Pre-training (InternImage-H)Validation 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