Transformer Decoders with MultiModal Regularization for Cross-Modal Food Retrieval Article Swipe
Mustafa Shukor
,
Guillaume Couairon
,
Asya Grechka
,
Matthieu Cord
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2204.09730
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2204.09730
Cross-modal image-recipe retrieval has gained significant attention in recent years. Most work focuses on improving cross-modal embeddings using unimodal encoders, that allow for efficient retrieval in large-scale databases, leaving aside cross-attention between modalities which is more computationally expensive. We propose a new retrieval framework, T-Food (Transformer Decoders with MultiModal Regularization for Cross-Modal Food Retrieval) that exploits the interaction between modalities in a novel regularization scheme, while using only unimodal encoders at test time for efficient retrieval. We also capture the intra-dependencies between recipe entities with a dedicated recipe encoder, and propose new variants of triplet losses with dynamic margins that adapt to the difficulty of the task. Finally, we leverage the power of the recent Vision and Language Pretraining (VLP) models such as CLIP for the image encoder. Our approach outperforms existing approaches by a large margin on the Recipe1M dataset. Specifically, we achieve absolute improvements of 8.1 % (72.6 R@1) and +10.9 % (44.6 R@1) on the 1k and 10k test sets respectively. The code is available here:https://github.com/mshukor/TFood
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2204.09730
- https://arxiv.org/pdf/2204.09730
- OA Status
- green
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4224312159
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4224312159Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2204.09730Digital Object Identifier
- Title
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Transformer Decoders with MultiModal Regularization for Cross-Modal Food RetrievalWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2022Year of publication
- Publication date
-
2022-04-20Full publication date if available
- Authors
-
Mustafa Shukor, Guillaume Couairon, Asya Grechka, Matthieu CordList of authors in order
- Landing page
-
https://arxiv.org/abs/2204.09730Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2204.09730Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2204.09730Direct OA link when available
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Computer science, Encoder, Modal, Transformer, Exploit, Regularization (linguistics), Leverage (statistics), Artificial intelligence, Information retrieval, Machine learning, Pattern recognition (psychology), Physics, Polymer chemistry, Operating system, Computer security, Quantum mechanics, Chemistry, VoltageTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
- Citations by year (recent)
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2023: 1Per-year citation counts (last 5 years)
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.databases, | 27 |
| abstract_inverted_index.difficulty | 103 |
| abstract_inverted_index.embeddings | 16 |
| abstract_inverted_index.expensive. | 37 |
| abstract_inverted_index.framework, | 43 |
| abstract_inverted_index.modalities | 32, 59 |
| abstract_inverted_index.retrieval. | 75 |
| abstract_inverted_index.Cross-Modal | 51 |
| abstract_inverted_index.Cross-modal | 0 |
| abstract_inverted_index.Pretraining | 118 |
| abstract_inverted_index.cross-modal | 15 |
| abstract_inverted_index.interaction | 57 |
| abstract_inverted_index.large-scale | 26 |
| abstract_inverted_index.outperforms | 130 |
| abstract_inverted_index.significant | 5 |
| abstract_inverted_index.(Transformer | 45 |
| abstract_inverted_index.image-recipe | 1 |
| abstract_inverted_index.improvements | 145 |
| abstract_inverted_index.Specifically, | 141 |
| abstract_inverted_index.respectively. | 163 |
| abstract_inverted_index.Regularization | 49 |
| abstract_inverted_index.regularization | 63 |
| abstract_inverted_index.computationally | 36 |
| abstract_inverted_index.cross-attention | 30 |
| abstract_inverted_index.intra-dependencies | 80 |
| abstract_inverted_index.here:https://github.com/mshukor/TFood | 168 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 4 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/2 |
| sustainable_development_goals[0].score | 0.5199999809265137 |
| sustainable_development_goals[0].display_name | Zero hunger |
| citation_normalized_percentile |