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SOTA
Semantic Segmentation
Semantic Segmentation On Scannetv2
Semantic Segmentation On Scannetv2
评估指标
Mean IoU
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
Mean IoU
Paper Title
Repository
PSPNet
47.5%
Pyramid Scene Parsing Network
CMX
61.3%
CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformers
AdapNet++
50.3
Self-Supervised Model Adaptation for Multimodal Semantic Segmentation
ENet
37.6%
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
ScanNet (2d proj)
33.0%
ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenes
SSMA
57.7
Self-Supervised Model Adaptation for Multimodal Semantic Segmentation
Floors are Flat
-
Floors are Flat: Leveraging Semantics for Real-Time Surface Normal Prediction
RFBNet
59.2%
RFBNet: Deep Multimodal Networks with Residual Fusion Blocks for RGB-D Semantic Segmentation
-
EMSAFormer
56.4%
Efficient Multi-Task Scene Analysis with RGB-D Transformers
EMSANet (2x ResNet-34 NBt1D, PanopticNDT version)
60.0%
PanopticNDT: Efficient and Robust Panoptic Mapping
3DMV (2d proj)
49.8%
3DMV: Joint 3D-Multi-View Prediction for 3D Semantic Scene Segmentation
MSeg1080_RVC
48.5%
MSeg: A Composite Dataset for Multi-domain Semantic Segmentation
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