mlsanityData to 7 Oct 2026

CurlingNet: Compositional Learning between Images and Text for Fashion IQ Data

arXiv 2003.12299 ↗First posted 27 Mar 2020cs.CVcited by 21

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Abstract (arXiv)

We present an approach named CurlingNet that can measure the semantic distance of composition of image-text embedding. In order to learn an effective image-text composition for the data in the fashion domain, our model proposes two key components as follows. First, the Delivery makes the transition of a source image in an embedding space. Second, the Sweeping emphasizes query-related components of fashion images in the embedding space. We utilize a channel-wise gating mechanism to make it possible. Our single model outperforms previous state-of-the-art image-text composition models including TIRG and FiLM. We participate in the first fashion-IQ challenge in ICCV 2019, for which ensemble of our model achieves one of the best performances.

Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 Mar 2020.

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Citing papers per year: 2021: 3; 2022: 1; 2023: 9; 2024: 3; 2025: 5.

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  1. 2023CompoDiff: Versatile Composed Image Retrieval With Latent Diffusioncited by 84
  2. 2023Sentence-level Prompts Benefit Composed Image Retrievalcited by 59
  3. 2023Composed Image Retrieval using Contrastive Learning and Task-oriented CLIP-based Featurescited by 52
  4. 2023CoVR-2: Automatic Data Construction for Composed Video Retrievalcited by 52
  5. 2023Data Roaming and Quality Assessment for Composed Image Retrievalcited by 45
  6. 2023Bi-directional Training for Composed Image Retrieval via Text Prompt Learningcited by 43
  7. 2024Knowledge-Enhanced Dual-stream Zero-shot Composed Image Retrievalcited by 36
  8. 2023Candidate Set Re-ranking for Composed Image Retrieval with Dual Multi-modal Encodercited by 35
  9. 2021Conversational Fashion Image Retrieval via Multiturn Natural Language Feedbackcited by 29
  10. 2021RTIC: Residual Learning for Text and Image Composition using Graph Convolutional Networkcited by 27
  11. 2023Language-only Efficient Training of Zero-shot Composed Image Retrievalcited by 27
  12. 2024Composed Video Retrieval via Enriched Context and Discriminative Embeddingscited by 26
9 more
  1. 2025Scale Up Composed Image Retrieval Learning via Modification Text Generationcited by 7
  2. 2025Beyond Simple Edits: Composed Video Retrieval with Dense Modificationscited by 6
  3. 2022Training and challenging models for text-guided fashion image retrievalcited by 5
  4. 2023Dual Relation Alignment for Composed Image Retrievalcited by 5
  5. 2024A Survey of Multimodal Composite Editing and Retrievalcited by 5
  6. 2025TMCIR: Token Merge Benefits Composed Image Retrievalcited by 4
  7. 2025PDV: Prompt Directional Vectors for Zero-shot Composed Image Retrievalcited by 3
  8. 2025Composed Multi-modal Retrieval: A Survey of Approaches and Applicationscited by 2
  9. 2021Cycled Compositional Learning between Images and Textcited by 1