EigeNet applies a cross-view alternate-attention transformer with geometry modulation for few-shot novel-view RIR prediction, reporting SOTA results on simulated and real data.
Few-shot audio-visual learning of environment acoustics,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.SD 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
EigeNet: Geometry-Informed Multi-Modal Learning for Few-shot Novel View RIR Prediction
EigeNet applies a cross-view alternate-attention transformer with geometry modulation for few-shot novel-view RIR prediction, reporting SOTA results on simulated and real data.