TasksSotADatasetsPapersMethodsSubmitAbout
Papers With Code 2

A community resource for machine learning research: papers, code, benchmarks, and state-of-the-art results.

Explore

Notable BenchmarksAll SotADatasetsPapersMethods

Community

Submit ResultsAbout

Data sourced from the PWC Archive (CC-BY-SA 4.0). Built by the community, for the community.

Papers/Fully Convolutional Networks for Panoptic Segmentation

Fully Convolutional Networks for Panoptic Segmentation

Yanwei Li, Hengshuang Zhao, Xiaojuan Qi, LiWei Wang, Zeming Li, Jian Sun, Jiaya Jia

2020-12-01CVPR 2021 1Panoptic SegmentationSegmentation
PaperPDFCodeCodeCode(official)Code(official)CodeCode

Abstract

In this paper, we present a conceptually simple, strong, and efficient framework for panoptic segmentation, called Panoptic FCN. Our approach aims to represent and predict foreground things and background stuff in a unified fully convolutional pipeline. In particular, Panoptic FCN encodes each object instance or stuff category into a specific kernel weight with the proposed kernel generator and produces the prediction by convolving the high-resolution feature directly. With this approach, instance-aware and semantically consistent properties for things and stuff can be respectively satisfied in a simple generate-kernel-then-segment workflow. Without extra boxes for localization or instance separation, the proposed approach outperforms previous box-based and -free models with high efficiency on COCO, Cityscapes, and Mapillary Vistas datasets with single scale input. Our code is made publicly available at https://github.com/Jia-Research-Lab/PanopticFCN.

Results

TaskDatasetMetricValueModel
Semantic SegmentationCityscapes valPQ61.4Panoptic FCN* (ResNet-FPN)
Semantic SegmentationCityscapes valPQth54.8Panoptic FCN* (ResNet-FPN)
Semantic SegmentationCityscapes valPQst70.6Panoptic FCN* (Swin-L, Cityscapes-fine)
Semantic SegmentationCityscapes valPQth59.5Panoptic FCN* (Swin-L, Cityscapes-fine)
Semantic SegmentationCityscapes valPQst66.6Panoptic FCN* (ResNet-50-FPN)
Semantic SegmentationMapillary valPQ45.7Panoptic FCN* (Swin-L, single-scale)
Semantic SegmentationMapillary valPQst52.1Panoptic FCN* (Swin-L, single-scale)
Semantic SegmentationMapillary valPQth40.8Panoptic FCN* (Swin-L, single-scale)
Semantic SegmentationMapillary valPQ36.9Panoptic FCN* (ResNet-FPN)
Semantic SegmentationMapillary valPQth32.9Panoptic FCN* (ResNet-FPN)
Semantic SegmentationMapillary valPQst42.3Panoptic FCN* (ResNet-50-FPN)
Semantic SegmentationCOCO test-devPQ52.7Panoptic FCN* (Swin-L)
Semantic SegmentationCOCO test-devPQth59.4Panoptic FCN* (Swin-L)
Semantic SegmentationCOCO test-devPQ47.5Panoptic FCN*++ (DCN-101-FPN)
Semantic SegmentationCOCO test-devPQst38.2Panoptic FCN*++ (DCN-101-FPN)
Semantic SegmentationCOCO test-devPQth53.7Panoptic FCN*++ (DCN-101-FPN)
Semantic SegmentationCOCO minivalPQ44.3Panoptic FCN* (ResNet-50-FPN)
Semantic SegmentationCOCO minivalPQst35.6Panoptic FCN* (ResNet-50-FPN)
Semantic SegmentationCOCO minivalPQth50Panoptic FCN* (ResNet-50-FPN)
Semantic SegmentationCOCO minivalRQ53Panoptic FCN* (ResNet-50-FPN)
Semantic SegmentationCOCO minivalRQst43.5Panoptic FCN* (ResNet-50-FPN)
Semantic SegmentationCOCO minivalRQth59.3Panoptic FCN* (ResNet-50-FPN)
Semantic SegmentationCOCO minivalSQ80.7Panoptic FCN* (ResNet-50-FPN)
Semantic SegmentationCOCO minivalSQst76.7Panoptic FCN* (ResNet-50-FPN)
Semantic SegmentationCOCO minivalSQth83.4Panoptic FCN* (ResNet-50-FPN)
Semantic SegmentationCOCO minivalPQth58.5Panoptic FCN* (Swin-L, single-scale)
Semantic SegmentationCOCO minivalRQ61.6Panoptic FCN* (Swin-L, single-scale)
Semantic SegmentationCOCO minivalRQst51.1Panoptic FCN* (Swin-L, single-scale)
Semantic SegmentationCOCO minivalRQth68.6Panoptic FCN* (Swin-L, single-scale)
Semantic SegmentationCOCO minivalSQ83.2Panoptic FCN* (Swin-L, single-scale)
Semantic SegmentationCOCO minivalSQst81.1Panoptic FCN* (Swin-L, single-scale)
Semantic SegmentationCOCO minivalSQth84.6Panoptic FCN* (Swin-L, single-scale)
10-shot image generationCityscapes valPQ61.4Panoptic FCN* (ResNet-FPN)
10-shot image generationCityscapes valPQth54.8Panoptic FCN* (ResNet-FPN)
10-shot image generationCityscapes valPQst70.6Panoptic FCN* (Swin-L, Cityscapes-fine)
10-shot image generationCityscapes valPQth59.5Panoptic FCN* (Swin-L, Cityscapes-fine)
10-shot image generationCityscapes valPQst66.6Panoptic FCN* (ResNet-50-FPN)
10-shot image generationMapillary valPQ45.7Panoptic FCN* (Swin-L, single-scale)
10-shot image generationMapillary valPQst52.1Panoptic FCN* (Swin-L, single-scale)
10-shot image generationMapillary valPQth40.8Panoptic FCN* (Swin-L, single-scale)
10-shot image generationMapillary valPQ36.9Panoptic FCN* (ResNet-FPN)
10-shot image generationMapillary valPQth32.9Panoptic FCN* (ResNet-FPN)
10-shot image generationMapillary valPQst42.3Panoptic FCN* (ResNet-50-FPN)
10-shot image generationCOCO test-devPQ52.7Panoptic FCN* (Swin-L)
10-shot image generationCOCO test-devPQth59.4Panoptic FCN* (Swin-L)
10-shot image generationCOCO test-devPQ47.5Panoptic FCN*++ (DCN-101-FPN)
10-shot image generationCOCO test-devPQst38.2Panoptic FCN*++ (DCN-101-FPN)
10-shot image generationCOCO test-devPQth53.7Panoptic FCN*++ (DCN-101-FPN)
10-shot image generationCOCO minivalPQ44.3Panoptic FCN* (ResNet-50-FPN)
10-shot image generationCOCO minivalPQst35.6Panoptic FCN* (ResNet-50-FPN)
10-shot image generationCOCO minivalPQth50Panoptic FCN* (ResNet-50-FPN)
10-shot image generationCOCO minivalRQ53Panoptic FCN* (ResNet-50-FPN)
10-shot image generationCOCO minivalRQst43.5Panoptic FCN* (ResNet-50-FPN)
10-shot image generationCOCO minivalRQth59.3Panoptic FCN* (ResNet-50-FPN)
10-shot image generationCOCO minivalSQ80.7Panoptic FCN* (ResNet-50-FPN)
10-shot image generationCOCO minivalSQst76.7Panoptic FCN* (ResNet-50-FPN)
10-shot image generationCOCO minivalSQth83.4Panoptic FCN* (ResNet-50-FPN)
10-shot image generationCOCO minivalPQth58.5Panoptic FCN* (Swin-L, single-scale)
10-shot image generationCOCO minivalRQ61.6Panoptic FCN* (Swin-L, single-scale)
10-shot image generationCOCO minivalRQst51.1Panoptic FCN* (Swin-L, single-scale)
10-shot image generationCOCO minivalRQth68.6Panoptic FCN* (Swin-L, single-scale)
10-shot image generationCOCO minivalSQ83.2Panoptic FCN* (Swin-L, single-scale)
10-shot image generationCOCO minivalSQst81.1Panoptic FCN* (Swin-L, single-scale)
10-shot image generationCOCO minivalSQth84.6Panoptic FCN* (Swin-L, single-scale)
Panoptic SegmentationCityscapes valPQ61.4Panoptic FCN* (ResNet-FPN)
Panoptic SegmentationCityscapes valPQth54.8Panoptic FCN* (ResNet-FPN)
Panoptic SegmentationCityscapes valPQst70.6Panoptic FCN* (Swin-L, Cityscapes-fine)
Panoptic SegmentationCityscapes valPQth59.5Panoptic FCN* (Swin-L, Cityscapes-fine)
Panoptic SegmentationCityscapes valPQst66.6Panoptic FCN* (ResNet-50-FPN)
Panoptic SegmentationMapillary valPQ45.7Panoptic FCN* (Swin-L, single-scale)
Panoptic SegmentationMapillary valPQst52.1Panoptic FCN* (Swin-L, single-scale)
Panoptic SegmentationMapillary valPQth40.8Panoptic FCN* (Swin-L, single-scale)
Panoptic SegmentationMapillary valPQ36.9Panoptic FCN* (ResNet-FPN)
Panoptic SegmentationMapillary valPQth32.9Panoptic FCN* (ResNet-FPN)
Panoptic SegmentationMapillary valPQst42.3Panoptic FCN* (ResNet-50-FPN)
Panoptic SegmentationCOCO test-devPQ52.7Panoptic FCN* (Swin-L)
Panoptic SegmentationCOCO test-devPQth59.4Panoptic FCN* (Swin-L)
Panoptic SegmentationCOCO test-devPQ47.5Panoptic FCN*++ (DCN-101-FPN)
Panoptic SegmentationCOCO test-devPQst38.2Panoptic FCN*++ (DCN-101-FPN)
Panoptic SegmentationCOCO test-devPQth53.7Panoptic FCN*++ (DCN-101-FPN)
Panoptic SegmentationCOCO minivalPQ44.3Panoptic FCN* (ResNet-50-FPN)
Panoptic SegmentationCOCO minivalPQst35.6Panoptic FCN* (ResNet-50-FPN)
Panoptic SegmentationCOCO minivalPQth50Panoptic FCN* (ResNet-50-FPN)
Panoptic SegmentationCOCO minivalRQ53Panoptic FCN* (ResNet-50-FPN)
Panoptic SegmentationCOCO minivalRQst43.5Panoptic FCN* (ResNet-50-FPN)
Panoptic SegmentationCOCO minivalRQth59.3Panoptic FCN* (ResNet-50-FPN)
Panoptic SegmentationCOCO minivalSQ80.7Panoptic FCN* (ResNet-50-FPN)
Panoptic SegmentationCOCO minivalSQst76.7Panoptic FCN* (ResNet-50-FPN)
Panoptic SegmentationCOCO minivalSQth83.4Panoptic FCN* (ResNet-50-FPN)
Panoptic SegmentationCOCO minivalPQth58.5Panoptic FCN* (Swin-L, single-scale)
Panoptic SegmentationCOCO minivalRQ61.6Panoptic FCN* (Swin-L, single-scale)
Panoptic SegmentationCOCO minivalRQst51.1Panoptic FCN* (Swin-L, single-scale)
Panoptic SegmentationCOCO minivalRQth68.6Panoptic FCN* (Swin-L, single-scale)
Panoptic SegmentationCOCO minivalSQ83.2Panoptic FCN* (Swin-L, single-scale)
Panoptic SegmentationCOCO minivalSQst81.1Panoptic FCN* (Swin-L, single-scale)
Panoptic SegmentationCOCO minivalSQth84.6Panoptic FCN* (Swin-L, single-scale)

Related Papers

SeC: Advancing Complex Video Object Segmentation via Progressive Concept Construction2025-07-21Deep Learning-Based Fetal Lung Segmentation from Diffusion-weighted MRI Images and Lung Maturity Evaluation for Fetal Growth Restriction2025-07-17DiffOSeg: Omni Medical Image Segmentation via Multi-Expert Collaboration Diffusion Model2025-07-17From Variability To Accuracy: Conditional Bernoulli Diffusion Models with Consensus-Driven Correction for Thin Structure Segmentation2025-07-17Unleashing Vision Foundation Models for Coronary Artery Segmentation: Parallel ViT-CNN Encoding and Variational Fusion2025-07-17SCORE: Scene Context Matters in Open-Vocabulary Remote Sensing Instance Segmentation2025-07-17Unified Medical Image Segmentation with State Space Modeling Snake2025-07-17A Privacy-Preserving Semantic-Segmentation Method Using Domain-Adaptation Technique2025-07-17