A gated dual-conditioning flow-matching model achieves 10 m→2 m cross-sensor super-resolution with a 38% FID reduction over the best baseline on a rare-landform (retrogressive thaw slump) benchmark.
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter
1 Pith paper cite this work, alongside 570 external citations. Polarity classification is still indexing.
1
Pith paper citing it
570
external citations · OpenAlex
fields
cs.CV 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Semantic-Guided Cross-Sensor Super Resolution of Remote Sensing Images: A Gated Dual Conditioning Flow Matching Model
A gated dual-conditioning flow-matching model achieves 10 m→2 m cross-sensor super-resolution with a 38% FID reduction over the best baseline on a rare-landform (retrogressive thaw slump) benchmark.