VISAGE: Video Instance Segmentation with Appearance-Guided Enhancement Article Swipe
Hanjung Kim
,
Jae-Hyun Kang
,
Miran Heo
,
Sukjun Hwang
,
Seoung Wug Oh
,
Seon Joo Kim
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2312.04885
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2312.04885
In recent years, online Video Instance Segmentation (VIS) methods have shown remarkable advancement with their powerful query-based detectors. Utilizing the output queries of the detector at the frame-level, these methods achieve high accuracy on challenging benchmarks. However, our observations demonstrate that these methods heavily rely on location information, which often causes incorrect associations between objects. This paper presents that a key axis of object matching in trackers is appearance information, which becomes greatly instructive under conditions where positional cues are insufficient for distinguishing their identities. Therefore, we suggest a simple yet powerful extension to object decoders that explicitly extract embeddings from backbone features and drive queries to capture the appearances of objects, which greatly enhances instance association accuracy. Furthermore, recognizing the limitations of existing benchmarks in fully evaluating appearance awareness, we have constructed a synthetic dataset to rigorously validate our method. By effectively resolving the over-reliance on location information, we achieve state-of-the-art results on YouTube-VIS 2019/2021 and Occluded VIS (OVIS). Code is available at https://github.com/KimHanjung/VISAGE.
Related Topics
Concepts
Computer science
Segmentation
Artificial intelligence
Key (lock)
Object (grammar)
BitTorrent tracker
Code (set theory)
Frame (networking)
Matching (statistics)
Computer vision
Source code
Extension (predicate logic)
Detector
Pattern recognition (psychology)
Information retrieval
Eye tracking
Set (abstract data type)
Programming language
Mathematics
Operating system
Telecommunications
Computer security
Statistics
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2312.04885
- https://arxiv.org/pdf/2312.04885
- OA Status
- green
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4389599500
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4389599500Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2312.04885Digital Object Identifier
- Title
-
VISAGE: Video Instance Segmentation with Appearance-Guided EnhancementWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-12-08Full publication date if available
- Authors
-
Hanjung Kim, Jae-Hyun Kang, Miran Heo, Sukjun Hwang, Seoung Wug Oh, Seon Joo KimList of authors in order
- Landing page
-
https://arxiv.org/abs/2312.04885Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2312.04885Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2312.04885Direct OA link when available
- Concepts
-
Computer science, Segmentation, Artificial intelligence, Key (lock), Object (grammar), BitTorrent tracker, Code (set theory), Frame (networking), Matching (statistics), Computer vision, Source code, Extension (predicate logic), Detector, Pattern recognition (psychology), Information retrieval, Eye tracking, Set (abstract data type), Programming language, Mathematics, Operating system, Telecommunications, Computer security, StatisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1Per-year citation counts (last 5 years)
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.axis | 61 |
| abstract_inverted_index.cues | 78 |
| abstract_inverted_index.from | 100 |
| abstract_inverted_index.have | 9, 131 |
| abstract_inverted_index.high | 31 |
| abstract_inverted_index.rely | 44 |
| abstract_inverted_index.that | 40, 58, 96 |
| abstract_inverted_index.with | 13 |
| abstract_inverted_index.(VIS) | 7 |
| abstract_inverted_index.Video | 4 |
| abstract_inverted_index.drive | 104 |
| abstract_inverted_index.fully | 126 |
| abstract_inverted_index.often | 49 |
| abstract_inverted_index.paper | 56 |
| abstract_inverted_index.shown | 10 |
| abstract_inverted_index.their | 14, 83 |
| abstract_inverted_index.these | 28, 41 |
| abstract_inverted_index.under | 74 |
| abstract_inverted_index.where | 76 |
| abstract_inverted_index.which | 48, 70, 112 |
| abstract_inverted_index.causes | 50 |
| abstract_inverted_index.object | 63, 94 |
| abstract_inverted_index.online | 3 |
| abstract_inverted_index.output | 20 |
| abstract_inverted_index.recent | 1 |
| abstract_inverted_index.simple | 89 |
| abstract_inverted_index.years, | 2 |
| abstract_inverted_index.(OVIS). | 159 |
| abstract_inverted_index.achieve | 30, 150 |
| abstract_inverted_index.becomes | 71 |
| abstract_inverted_index.between | 53 |
| abstract_inverted_index.capture | 107 |
| abstract_inverted_index.dataset | 135 |
| abstract_inverted_index.extract | 98 |
| abstract_inverted_index.greatly | 72, 113 |
| abstract_inverted_index.heavily | 43 |
| abstract_inverted_index.method. | 140 |
| abstract_inverted_index.methods | 8, 29, 42 |
| abstract_inverted_index.queries | 21, 105 |
| abstract_inverted_index.results | 152 |
| abstract_inverted_index.suggest | 87 |
| abstract_inverted_index.However, | 36 |
| abstract_inverted_index.Instance | 5 |
| abstract_inverted_index.Occluded | 157 |
| abstract_inverted_index.accuracy | 32 |
| abstract_inverted_index.backbone | 101 |
| abstract_inverted_index.decoders | 95 |
| abstract_inverted_index.detector | 24 |
| abstract_inverted_index.enhances | 114 |
| abstract_inverted_index.existing | 123 |
| abstract_inverted_index.features | 102 |
| abstract_inverted_index.instance | 115 |
| abstract_inverted_index.location | 46, 147 |
| abstract_inverted_index.matching | 64 |
| abstract_inverted_index.objects, | 111 |
| abstract_inverted_index.objects. | 54 |
| abstract_inverted_index.powerful | 15, 91 |
| abstract_inverted_index.presents | 57 |
| abstract_inverted_index.trackers | 66 |
| abstract_inverted_index.validate | 138 |
| abstract_inverted_index.2019/2021 | 155 |
| abstract_inverted_index.Utilizing | 18 |
| abstract_inverted_index.accuracy. | 117 |
| abstract_inverted_index.available | 162 |
| abstract_inverted_index.extension | 92 |
| abstract_inverted_index.incorrect | 51 |
| abstract_inverted_index.resolving | 143 |
| abstract_inverted_index.synthetic | 134 |
| abstract_inverted_index.Therefore, | 85 |
| abstract_inverted_index.appearance | 68, 128 |
| abstract_inverted_index.awareness, | 129 |
| abstract_inverted_index.benchmarks | 124 |
| abstract_inverted_index.conditions | 75 |
| abstract_inverted_index.detectors. | 17 |
| abstract_inverted_index.embeddings | 99 |
| abstract_inverted_index.evaluating | 127 |
| abstract_inverted_index.explicitly | 97 |
| abstract_inverted_index.positional | 77 |
| abstract_inverted_index.remarkable | 11 |
| abstract_inverted_index.rigorously | 137 |
| abstract_inverted_index.YouTube-VIS | 154 |
| abstract_inverted_index.advancement | 12 |
| abstract_inverted_index.appearances | 109 |
| abstract_inverted_index.association | 116 |
| abstract_inverted_index.benchmarks. | 35 |
| abstract_inverted_index.challenging | 34 |
| abstract_inverted_index.constructed | 132 |
| abstract_inverted_index.demonstrate | 39 |
| abstract_inverted_index.effectively | 142 |
| abstract_inverted_index.identities. | 84 |
| abstract_inverted_index.instructive | 73 |
| abstract_inverted_index.limitations | 121 |
| abstract_inverted_index.query-based | 16 |
| abstract_inverted_index.recognizing | 119 |
| abstract_inverted_index.Furthermore, | 118 |
| abstract_inverted_index.Segmentation | 6 |
| abstract_inverted_index.associations | 52 |
| abstract_inverted_index.frame-level, | 27 |
| abstract_inverted_index.information, | 47, 69, 148 |
| abstract_inverted_index.insufficient | 80 |
| abstract_inverted_index.observations | 38 |
| abstract_inverted_index.over-reliance | 145 |
| abstract_inverted_index.distinguishing | 82 |
| abstract_inverted_index.state-of-the-art | 151 |
| abstract_inverted_index.https://github.com/KimHanjung/VISAGE. | 164 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 6 |
| citation_normalized_percentile |