Instance Segmentation On Cityscapes

Résultats

Résultats de performance de divers modèles sur ce benchmark

	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
Modèle 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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