TIMO improves training-free CLIP few-shot classification by mutually guiding text and image features, and a tuned variant TIMO-S reports state-of-the-art accuracy with roughly 100x less time than training-required methods.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2024 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Text and Image Are Mutually Beneficial: Enhancing Training-Free Few-Shot Classification with CLIP
TIMO improves training-free CLIP few-shot classification by mutually guiding text and image features, and a tuned variant TIMO-S reports state-of-the-art accuracy with roughly 100x less time than training-required methods.