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Semantic Segmentation On Sun Rgbd

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Mean IoU (test)

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Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Paper Title
DFormer-L48.17Missing Modality Robustness in Semi-Supervised Multi-Modal Semantic Segmentation
CMX (B5)-Efficient RGB-D Semantic Segmentation for Indoor Scene Analysis
EMSANet (2x ResNet-34 NBt1D, PanopticNDT version, finetuned)-Context Contrasted Feature and Gated Multi-Scale Aggregation for Scene Segmentation
CMX (B4)-CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformers
FSFNet-Deep feature selection-and-fusion for RGB-D semantic segmentation
TokenFusion (S)-Spatial Information Guided Convolution for Real-Time RGBD Semantic Segmentation
TokenFusion (S)-Depth-aware CNN for RGB-D Segmentation
PSD-ResNet50-ShapeConv: Shape-aware Convolutional Layer for Indoor RGB-D Semantic Segmentation
DFormer-B-RDFNet: RGB-D Multi-Level Residual Feature Fusion for Indoor Semantic Segmentation
EMSANet (2x ResNet-34 NBt1D, PanopticNDT version, finetuned)-PanopticNDT: Efficient and Robust Panoptic Mapping
GeminiFusion (MiT-B5)-GeminiFusion: Efficient Pixel-wise Multimodal Fusion for Vision Transformer
DFormer-L-Attention-guided Chained Context Aggregation for Semantic Segmentation
TokenFusion (S)-Multimodal Token Fusion for Vision Transformers
TokenFusion (Ti)-Bi-directional Cross-Modality Feature Propagation with Separation-and-Aggregation Gate for RGB-D Semantic Segmentation
DFormer-L-DFormer: Rethinking RGBD Representation Learning for Semantic Segmentation
DPLNet -Self-Supervised Model Adaptation for Multimodal Semantic Segmentation
DPLNet -Efficient Multimodal Semantic Segmentation via Dual-Prompt Learning
TokenFusion (Ti)-Multimodal Token Fusion for Vision Transformers
CMX (B4)-Pixel Difference Convolutional Network for RGB-D Semantic Segmentation
DPLNet -Recurrent Scene Parsing with Perspective Understanding in the Loop
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Semantic Segmentation On Sun Rgbd | SOTA | HyperAI