BiCLIP: Domain Canonicalization via Structured Geometric Transformation
Recent advances in vision-language models (VLMs) have demonstrated remarkable zero-shot capabilities, yet adapting these models to specialized domains remains a significant challenge. Building on recent theoretical insights suggesting that independently trained VLMs are related by a canonical transformation, we extend this understanding to the concept of domains. We hypothesize that image features across disparate domains are related by a canonicalized geometric transformation that can be recovered using a small set of anchors. Few-shot classification provides a natural setting for this alignment, as the limited labeled samples serve as the anchors required to estimate this transformation...
| Authors | Pranav Mantini, Shishir K. Shah |
|---|---|
| Primary category | cs.CV |
| Published | 9 March 2026 |
| Last updated at source | 11 April 2026 |
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