You'll Never Walk Alone: A Sketch and Text Duet for Fine-Grained Image Retrieval
<|reference_start|>You'll Never Walk Alone: A Sketch and Text Duet for Fine-Grained Image Retrieval: Two primary input modalities prevail in image retrieval: sketch and text. While text is widely used for inter-category retrieval tasks, sketches have been established as the sole preferred modality for fine-grained image retrieval due to their ability to capture intricate visual details. In this paper, we question the reliance on sketches alone for fine-grained image retrieval by simultaneously exploring the fine-grained representation capabilities of both sketch and text, orchestrating a duet between the two. The end result enables precise retrievals previously unattainable, allowing users to pose ever-finer queries and incorporate attributes like colour and contextual cues from text. For this purpose, we introduce a novel compositionality framework, effectively combining sketches and text using pre-trained CLIP models, while eliminating the need for extensive fine-grained textual descriptions. Last but not least, our system extends to novel applications in composed image retrieval, domain attribute transfer, and fine-grained generation, providing solutions for various real-world scenarios.<|reference_end|>
@article{koley2024you'll,
    title={You'll Never Walk Alone: A Sketch and Text Duet for Fine-Grained Image
  Retrieval},
    author={Subhadeep Koley, Ayan Kumar Bhunia, Aneeshan Sain, Pinaki Nath
  Chowdhury, Tao Xiang, Yi-Zhe Song},
    journal={arXiv preprint arXiv:2403.07222},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.07222},
    primaryClass={cs.CV}
}