A fast CU partition algorithm of ERP 360‐degree video based on deep learning Article Swipe
Hai Xiang
,
Fen Chen
,
Zongju Peng
,
Lian Huang
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1049/ell2.70129
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1049/ell2.70129
This article proposes a deep‐learning‐based fast coding unit (CU) partition algorithm to reduce encoding time of equirectangular projection (ERP) 360‐degree videos in versatile video coding. First, an ERP 360‐degree dataset with ERP latitude characteristics and quantitative parameter characteristics is established. Then, a lightweight prediction partition convolutional neural network is designed to predict the partition probability of 44 CU edges in 3232 luminance CU. Finally, an intra prediction decision‐making scheme is developed to reduce the number of candidate modes of CUs with size equal to or smaller than 3232, thereby achieving fast encoding. Experimental results show that the proposed method saves 58.51% of encoding time in All Intra configuration and only increases Bjontegaard delta bit‐rate by 1.39%.
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Metadata
- Type
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- Language
- en
- Landing Page
- https://doi.org/10.1049/ell2.70129
- OA Status
- gold
- Cited By
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- References
- 8
- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
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https://openalex.org/W4405988324Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1049/ell2.70129Digital Object Identifier
- Title
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A fast CU partition algorithm of ERP 360‐degree video based on deep learningWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
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2025-01-01Full publication date if available
- Authors
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Hai Xiang, Fen Chen, Zongju Peng, Lian HuangList of authors in order
- Landing page
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https://doi.org/10.1049/ell2.70129Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.1049/ell2.70129Direct OA link when available
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Partition (number theory), Degree (music), Computer science, Algorithm, Artificial intelligence, Deep learning, Pattern recognition (psychology), Mathematics, Combinatorics, Acoustics, PhysicsTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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2025: 1Per-year citation counts (last 5 years)
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8Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.latitude | 33 |
| abstract_inverted_index.proposed | 98 |
| abstract_inverted_index.proposes | 3 |
| abstract_inverted_index.achieving | 90 |
| abstract_inverted_index.algorithm | 11 |
| abstract_inverted_index.candidate | 77 |
| abstract_inverted_index.developed | 71 |
| abstract_inverted_index.encoding. | 92 |
| abstract_inverted_index.increases | 111 |
| abstract_inverted_index.luminance | 62 |
| abstract_inverted_index.parameter | 37 |
| abstract_inverted_index.partition | 10, 45, 54 |
| abstract_inverted_index.versatile | 23 |
| abstract_inverted_index.bit‐rate | 114 |
| abstract_inverted_index.prediction | 44, 67 |
| abstract_inverted_index.projection | 18 |
| abstract_inverted_index.Bjontegaard | 112 |
| abstract_inverted_index.lightweight | 43 |
| abstract_inverted_index.probability | 55 |
| abstract_inverted_index.360‐degree | 20, 29 |
| abstract_inverted_index.Experimental | 93 |
| abstract_inverted_index.established. | 40 |
| abstract_inverted_index.quantitative | 36 |
| abstract_inverted_index.configuration | 108 |
| abstract_inverted_index.convolutional | 46 |
| abstract_inverted_index.characteristics | 34, 38 |
| abstract_inverted_index.equirectangular | 17 |
| abstract_inverted_index.decision‐making | 68 |
| abstract_inverted_index.deep‐learning‐based | 5 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 91 |
| corresponding_author_ids | https://openalex.org/A5055084879 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| corresponding_institution_ids | https://openalex.org/I50632499 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/16 |
| sustainable_development_goals[0].score | 0.800000011920929 |
| sustainable_development_goals[0].display_name | Peace, Justice and strong institutions |
| citation_normalized_percentile.value | 0.81363025 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |