Papers › "This is my unicorn, Fluffy": Personalizing frozen vision-language representations
"This is my unicorn, Fluffy": Personalizing frozen vision-language representations
Niv Cohen, Rinon Gal, Eli A. Meirom, Gal Chechik, Yuval Atzmon
Large Vision & Language models pretrained on web-scale data provide representations that are invaluable for numerous V&L problems. However, it is unclear how they can be used for reasoning about user-specific visual concepts in unstructured language. This problem arises in multiple domains, from personalized image retrieval to personalized interaction with smart devices. We introduce a new learning setup called Personalized Vision & Language (PerVL) with two new benchmark datasets for retrieving and segmenting user-specific "personalized" concepts "in the wild". In PerVL, one should learn personalized concepts (1) independently of the downstream task (2) allowing a pretrained model to reason about them with free language, and (3) does not require personalized negative examples. We propose an architecture for solving PerVL that operates by extending the input vocabulary of a pretrained model with new word embeddings for the new personalized concepts. The model can then reason about them by simply using them in a sentence. We demonstrate that our approach learns personalized visual concepts from a few examples and can effectively apply them in image retrieval and semantic segmentation using rich textual queries.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Zero-Shot Composed Image Retrieval (ZS-CIR) | CIRCO | PALAVRA | mAP@10 | 5.32 | #43 of 43 | Archive leaderboard | report |
| Zero-Shot Composed Image Retrieval (ZS-CIR) | CIRR | PALAVRA | R@5 | 43.49 | #47 of 47 | Archive leaderboard | report |
| Zero-Shot Composed Image Retrieval (ZS-CIR) | Fashion IQ | PALAVRA | (Recall@10+Recall@50)/2 | 28.51 | #40 of 41 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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