Panoptic Segmentation
Panoptic segmentation unifies the typically distinct tasks of semantic segmentation (assign a class label to each pixel) and instance segmentation (detect and segment each object instance).
( Image credit: Detectron2 )
Leaderboards
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Greatest papers with code
SOLOv2: Dynamic, Faster and Stronger
• aim-uofa/adet
• 
Importantly, we take one step further by dynamically learning the mask head of the object segmenter such that the mask head is conditioned on the location.
#5 best model for
Instance Segmentation
on COCO test-dev
INSTANCE SEGMENTATION OBJECT DETECTION PANOPTIC SEGMENTATION
UPSNet: A Unified Panoptic Segmentation Network
CVPR 2019
• uber-research/UPSNet
•
More importantly, we introduce a parameter-free panoptic head which solves the panoptic segmentation via pixel-wise classification.
#3 best model for
Panoptic Segmentation
on Cityscapes val
(using extra training data)
CenterMask : Real-Time Anchor-Free Instance Segmentation
arXiv 2019
• youngwanLEE/CenterMask
•
We hope that CenterMask and VoVNetV2 can serve as a solid baseline of real-time instance segmentation and backbone network for various vision tasks, respectively.
PANOPTIC SEGMENTATION REAL-TIME INSTANCE SEGMENTATION REAL-TIME OBJECT DETECTION
AdaptIS: Adaptive Instance Selection Network
ICCV 2019
• saic-vul/adaptis
• 
Given an input image and a point $(x, y)$, it generates a mask for the object located at $(x, y)$.
#2 best model for
Panoptic Segmentation
on Cityscapes val
Seamless Scene Segmentation
CVPR 2019
• mapillary/seamseg
•
In this work we introduce a novel, CNN-based architecture that can be trained end-to-end to deliver seamless scene segmentation results.
Panoptic Segmentation
We propose and study a task we name panoptic segmentation (PS).
#4 best model for
Panoptic Segmentation
on Cityscapes val
(using extra training data)
INSTANCE SEGMENTATION PANOPTIC SEGMENTATION SCENE PARSING SCENE SEGMENTATION
Weakly- and Semi-Supervised Panoptic Segmentation
We present a weakly supervised model that jointly performs both semantic- and instance-segmentation -- a particularly relevant problem given the substantial cost of obtaining pixel-perfect annotation for these tasks.
#13 best model for
Panoptic Segmentation
on Cityscapes val
INSTANCE SEGMENTATION PANOPTIC SEGMENTATION WEAKLY-SUPERVISED INSTANCE SEGMENTATION WEAKLY-SUPERVISED PANOPTIC SEGMENTATION WEAKLY-SUPERVISED SEMANTIC SEGMENTATION
SOGNet: Scene Overlap Graph Network for Panoptic Segmentation
In order to overcome the lack of supervision, we introduce a differentiable module to resolve the overlap between any pair of instances.
Single Network Panoptic Segmentation for Street Scene Understanding
• DdeGeus/single-network-panoptic-segmentation
• 
Our network is evaluated on two street scene datasets: Cityscapes and Mapillary Vistas.
INSTANCE SEGMENTATION PANOPTIC SEGMENTATION SCENE UNDERSTANDING
Generator evaluator-selector net: a modular approach for panoptic segmentation
• sagieppel/Generator-evaluator-selector-net-a-modular-approach-for-panoptic-segmentation
•
The generator/evaluator approach for this case consists of two independent convolutional neural nets: a generator net that suggests variety segments corresponding to objects and distinct regions in the image and an evaluator net that chooses the best segments to be merged into the segmentation map.