HyperAI

Semantic Segmentation On Mcubes

Metrics

mIoU

Results

Performance results of various models on this benchmark

Model Name
mIoU
Paper TitleRepository
DRConv (RGB-A-D-N)34.63%Dynamic Region-Aware Convolution-
StitchFusion (RGB-A)52.68StitchFusion: Weaving Any Visual Modalities to Enhance Multimodal Semantic Segmentation
DeepLabV3+ (RGB-A-D-N)38.13%Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
StitchFusion (RGB-A-D-N)53.92StitchFusion: Weaving Any Visual Modalities to Enhance Multimodal Semantic Segmentation
ShareCMP (B2 RGB-A-D)50.99%ShareCMP: Polarization-Aware RGB-P Semantic Segmentation
CMNeXt (B2 RGB-A-D-N)51.54%Delivering Arbitrary-Modal Semantic Segmentation
MMSFormer (RGB-A-D-N)53.11%MMSFormer: Multimodal Transformer for Material and Semantic Segmentation
StitchFusion (RGB-N)53.21StitchFusion: Weaving Any Visual Modalities to Enhance Multimodal Semantic Segmentation
ShareCMP(B2 RGB-A)50.34ShareCMP: Polarization-Aware RGB-P Semantic Segmentation
StitchFusion (RGB-A-D)53.26StitchFusion: Weaving Any Visual Modalities to Enhance Multimodal Semantic Segmentation
MMSFormer (RGB-A)51.30%MMSFormer: Multimodal Transformer for Material and Semantic Segmentation
MemorySAM-B+(RGB-A-D)52.20MemorySAM: Memorize Modalities and Semantics with Segment Anything Model 2 for Multi-modal Semantic Segmentation
MMSFormer (RGB)50.44%MMSFormer: Multimodal Transformer for Material and Semantic Segmentation
MMSFormer (RGB-A-D)52.05%MMSFormer: Multimodal Transformer for Material and Semantic Segmentation
ShareCMP(B2 RGB-D)50.55ShareCMP: Polarization-Aware RGB-P Semantic Segmentation
DDF (RGB-A-D-N)36.16%Decoupled Dynamic Filter Networks
CMNeXt (B2 RGB-A-D)49.48%Delivering Arbitrary-Modal Semantic Segmentation
CMNeXt (B2 RGB-A)48.42%Delivering Arbitrary-Modal Semantic Segmentation
StitchFusion (RGB-D)52.72StitchFusion: Weaving Any Visual Modalities to Enhance Multimodal Semantic Segmentation
MemorySAM-B+(RGB-A-D-N)52.88MemorySAM: Memorize Modalities and Semantics with Segment Anything Model 2 for Multi-modal Semantic Segmentation
0 of 22 row(s) selected.