An End-to-End Network for Panoptic Segmentation Article Swipe

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Huanyu Liu , Chao Peng , Changqian Yu , Jingbo Wang , Xu Liu , Gang Yu , Wei Jiang ·

YOU? · · 2019 · Open Access · · DOI: https://doi.org/10.48550/arxiv.1903.05027

Panoptic segmentation, which needs to assign a category label to each pixel and segment each object instance simultaneously, is a challenging topic. Traditionally, the existing approaches utilize two independent models without sharing features, which makes the pipeline inefficient to implement. In addition, a heuristic method is usually employed to merge the results. However, the overlapping relationship between object instances is difficult to determine without sufficient context information during the merging process. To address the problems, we propose a novel end-to-end network for panoptic segmentation, which can efficiently and effectively predict both the instance and stuff segmentation in a single network. Moreover, we introduce a novel spatial ranking module to deal with the occlusion problem between the predicted instances. Extensive experiments have been done to validate the performance of our proposed method and promising results have been achieved on the COCO Panoptic benchmark.

Related Topics

Computer Science

Segmentation Fault

Artificial Intelligence

Panopticon

Benchmark (Surveying)

Concepts

Computer science Segmentation Artificial intelligence Merge (version control) Panopticon Context (archaeology) Benchmark (surveying) Pipeline (software) Process (computing) Data mining Computer vision Information retrieval Geography Law Political science Biology Paleontology Geodesy Programming language Operating system Politics

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Type: preprint
Language: en
Landing Page: http://arxiv.org/abs/1903.05027
PDF: https://arxiv.org/pdf/1903.05027
OA Status: green
Cited By: 22
References: 47
Related Works: 10
OpenAlex ID: https://openalex.org/W2922314456

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DOI: https://doi.org/10.48550/arxiv.1903.05027

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Title: An End-to-End Network for Panoptic Segmentation

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Type: preprint

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Language: en

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Publication year: 2019

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Publication date: 2019-03-12

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Authors: Huanyu Liu, Chao Peng, Changqian Yu, Jingbo Wang, Xu Liu, Gang Yu, Wei Jiang

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Landing page: https://arxiv.org/abs/1903.05027

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PDF URL: https://arxiv.org/pdf/1903.05027

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OA status: green

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OA URL: https://arxiv.org/pdf/1903.05027

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Concepts: Computer science, Segmentation, Artificial intelligence, Merge (version control), Panopticon, Context (archaeology), Benchmark (surveying), Pipeline (software), Process (computing), Data mining, Computer vision, Information retrieval, Geography, Law, Political science, Biology, Paleontology, Geodesy, Programming language, Operating system, Politics

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Cited by: 22

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Citations by year (recent): 2023: 2, 2022: 1, 2021: 7, 2020: 6, 2019: 5

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abstract_inverted_index.sharing	31
abstract_inverted_index.spatial	105
abstract_inverted_index.usually	46
abstract_inverted_index.utilize	26
abstract_inverted_index.without	30, 63
abstract_inverted_index.However,	52
abstract_inverted_index.Panoptic	0, 140
abstract_inverted_index.achieved	136
abstract_inverted_index.category	7
abstract_inverted_index.employed	47
abstract_inverted_index.existing	24
abstract_inverted_index.instance	16, 92
abstract_inverted_index.network.	99
abstract_inverted_index.panoptic	82
abstract_inverted_index.pipeline	36
abstract_inverted_index.process.	70
abstract_inverted_index.proposed	129
abstract_inverted_index.results.	51
abstract_inverted_index.validate	124
abstract_inverted_index.Extensive	118
abstract_inverted_index.Moreover,	100
abstract_inverted_index.addition,	41
abstract_inverted_index.determine	62
abstract_inverted_index.difficult	60
abstract_inverted_index.features,	32
abstract_inverted_index.heuristic	43
abstract_inverted_index.instances	58
abstract_inverted_index.introduce	102
abstract_inverted_index.occlusion	112
abstract_inverted_index.predicted	116
abstract_inverted_index.problems,	74
abstract_inverted_index.promising	132
abstract_inverted_index.approaches	25
abstract_inverted_index.benchmark.	141
abstract_inverted_index.end-to-end	79
abstract_inverted_index.implement.	39
abstract_inverted_index.instances.	117
abstract_inverted_index.sufficient	64
abstract_inverted_index.challenging	20
abstract_inverted_index.effectively	88
abstract_inverted_index.efficiently	86
abstract_inverted_index.experiments	119
abstract_inverted_index.independent	28
abstract_inverted_index.inefficient	37
abstract_inverted_index.information	66
abstract_inverted_index.overlapping	54
abstract_inverted_index.performance	126
abstract_inverted_index.relationship	55
abstract_inverted_index.segmentation	95
abstract_inverted_index.segmentation,	1, 83
abstract_inverted_index.Traditionally,	22
abstract_inverted_index.simultaneously,	17
cited_by_percentile_year
countries_distinct_count	0
institutions_distinct_count	7
citation_normalized_percentile