Image Retrieval on Real-life Images with Pre-trained Vision-and-Language Models
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Cited by 43 in Multimodal LLMs / vision-language models, but placed by its own abstract, which didn’t fit.
Abstract (arXiv)
We extend the task of composed image retrieval, where an input query consists of an image and short textual description of how to modify the image. Existing methods have only been applied to non-complex images within narrow domains, such as fashion products, thereby limiting the scope of study on in-depth visual reasoning in rich image and language contexts. To address this issue, we collect the Compose Image Retrieval on Real-life images (CIRR) dataset, which consists of over 36,000 pairs of crowd-sourced, open-domain images with human-generated modifying text. To extend current methods to the open-domain, we propose CIRPLANT, a transformer based model that leverages rich pre-trained vision-and-language (V&L) knowledge for modifying visual features conditioned on natural language. Retrieval is then done by nearest neighbor lookup on the modified features. We demonstrate that with a relatively simple architecture, CIRPLANT outperforms existing methods on open-domain images, while matching state-of-the-art accuracy on the existing narrow datasets, such as fashion. Together with the release of CIRR, we believe this work will inspire further research on composed image retrieval.
Key facts. Cited by 244 papers in the map (data through 7 Oct 2026). Builds on 29 of its 44 references that are in the map. First posted on arXiv 9 Aug 2021.
Builds on
29 of 44 references.
References · 29
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- 2020Oscar: Object-Semantics Aligned Pre-training for Vision-Language Taskscited by 1,213
- 2018A Corpus for Reasoning About Natural Language Grounded in Photographscited by 457
- 2017A simple neural network module for relational reasoningcited by 345
- 2020A Recurrent Vision-and-Language BERT for Navigationcited by 300
- 2018Deep Face Recognition: A Surveycited by 275
- 2018Composing Text and Image for Image Retrieval - An Empirical Odysseycited by 234
- 2017Automatic Spatially-aware Fashion Concept Discoverycited by 132
- 2018Multilevel Language and Vision Integration for Text-to-Clip Retrievalcited by 128
- 2018Learning to Describe Differences Between Pairs of Similar Imagescited by 114
- 2018Dialog-based Interactive Image Retrievalcited by 84
- 2017Tips and Tricks for Visual Question Answering: Learnings from the 2017 Challengecited by 76
- 2017Convolutional Image Captioningcited by 52
- 2020Modality-Agnostic Attention Fusion for visual search with text feedbackcited by 51
- 2016Multimodal Residual Learning for Visual QAcited by 42
- 2019Fashion IQ: A New Dataset Towards Retrieving Images by Natural Language Feedbackcited by 42
- 2019Neural Naturalist: Generating Fine-Grained Image Comparisonscited by 36
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Citing papers per year: 2021: 2; 2022: 9; 2023: 39; 2024: 50; 2025: 70; 2026: 74.
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