MuRF fuses multi-resolution features from frozen vision foundation models at inference time to create stronger representations without any training.
We then apply a random rotationR(θ)with zero-padding, whereθ∼𝒰(−2.5 ◦, 2.5◦)with probability p=0.5 , followed by a random horizontal flip withp=0.5
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
MuRF: Unlocking the Multi-Scale Potential of Vision Foundation Models
MuRF fuses multi-resolution features from frozen vision foundation models at inference time to create stronger representations without any training.