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SOTA
Semantische Segmentierung
Semantic Segmentation On Densepass
Semantic Segmentation On Densepass
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mIoU
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Columns
Modellname
mIoU
Paper Title
Repository
PVT (Tiny, FPN)
31.20%
Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions
SwiftNet (Merge3)
32.04%
ISSAFE: Improving Semantic Segmentation in Accidents by Fusing Event-based Data
CLAN
31.46%
Taking A Closer Look at Domain Shift: Category-level Adversaries for Semantics Consistent Domain Adaptation
ERFNet
16.65%
ERFNet: Efficient Residual Factorized ConvNet for Real-time Semantic Segmentation
Seamless (Mapillary)
34.14%
Seamless Scene Segmentation
Trans4PASS+ (multi-scale)
57.23%
Behind Every Domain There is a Shift: Adapting Distortion-aware Vision Transformers for Panoramic Semantic Segmentation
SIM
44.58%
Differential Treatment for Stuff and Things: A Simple Unsupervised Domain Adaptation Method for Semantic Segmentation
SegFormer (MiT-B1)
38.5%
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers
SETR (MLA, Transformer-L)
35.6%
Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers
Trans4PASS (single-scale)
55.25%
Bending Reality: Distortion-aware Transformers for Adapting to Panoramic Semantic Segmentation
Trans4PASS+ (single-scale)
56.45%
Behind Every Domain There is a Shift: Adapting Distortion-aware Vision Transformers for Panoramic Semantic Segmentation
DANet (ResNet-101)
28.5%
Dual Attention Network for Scene Segmentation
Fast-SCNN
24.6%
Fast-SCNN: Fast Semantic Segmentation Network
ECANet
43.02%
Capturing Omni-Range Context for Omnidirectional Segmentation
SegFormer (MiT-B2)
42.4%
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers
USSS (Mapillary)
30.87%
Universal Semi-Supervised Semantic Segmentation
USSS (IDD)
26.98%
Universal Semi-Supervised Semantic Segmentation
PCS
53.83%
Prototypical Cross-domain Self-supervised Learning for Few-shot Unsupervised Domain Adaptation
DNL (ResNet-101)
32.1%
Disentangled Non-Local Neural Networks
ASMLP (MiT-B1)
42.05%
AS-MLP: An Axial Shifted MLP Architecture for Vision
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Semantic Segmentation On Densepass | SOTA | HyperAI