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SOTA
Instanzsegmentierung
Instance Segmentation On Cityscapes
Instance Segmentation On Cityscapes
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Columns
Modellname
Paper Title
Learnable Margin
Instance Segmentation by Jointly Optimizing Spatial Embeddings and Clustering Bandwidth
Dynamically Instantiated Network
Pixelwise Instance Segmentation with a Dynamically Instantiated Network
Panoptic-DeepLab [Cityscapes-fine]
Panoptic-DeepLab: A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic Segmentation
Modell 4
Track to Detect and Segment: An Online Multi-Object Tracker
Semantic Instance Segmentation with a Discriminative Loss Function
Semantic Instance Segmentation with a Discriminative Loss Function
EfficientPS
EfficientPS: Efficient Panoptic Segmentation
Instance Segmentation by Jointly Optimizing Spatial Embeddings and Clustering Bandwidth
Instance Segmentation by Jointly Optimizing Spatial Embeddings and Clustering Bandwidth
Panoptic-DeepLab [Mapillary Vistas]
Panoptic-DeepLab: A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic Segmentation
Deep Watershed Transform
Deep Watershed Transform for Instance Segmentation
GAIS-Net
Geometry-Aware Instance Segmentation with Disparity Maps
PolyTransform
PolyTransform: Deep Polygon Transformer for Instance Segmentation
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Instance Segmentation On Cityscapes | SOTA | HyperAI