ART is a neural network that iteratively estimates coarse-to-fine image transformations via an auto-regressive pipeline with hierarchical features and cross-attention guidance for robust alignment under sparse features and large deformations.
Decoupled weight decay reg- ularization, 2019
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.CV 2representative citing papers
MatRes jointly optimizes restoration and correspondence estimation at test time by enforcing conditional similarity on a single image pair and adapting lightweight modules without offline training.
citing papers explorer
-
Auto-regressive transformation for image alignment
ART is a neural network that iteratively estimates coarse-to-fine image transformations via an auto-regressive pipeline with hierarchical features and cross-attention guidance for robust alignment under sparse features and large deformations.
-
MatRes: Zero-Shot Test-Time Model Adaptation for Simultaneous Matching and Restoration
MatRes jointly optimizes restoration and correspondence estimation at test time by enforcing conditional similarity on a single image pair and adapting lightweight modules without offline training.