Domain adaptation via synthetic manuscript images improves OMR performance on real-world piano manuscripts without requiring in-domain symbols.
LiDAR light scattering augmentation (LISA): Physics- based simulation of adverse weather conditions for 3D object detection
6 Pith papers cite this work. Polarity classification is still indexing.
citation-role summary
citation-polarity summary
years
2026 6roles
dataset 1polarities
use dataset 1representative citing papers
NeuralLVC achieves better lossless compression than H.264 and H.265 on video sequences by combining masked diffusion with temporal conditioning on frame differences.
QnRL is a distributional quantum RL framework that distills conditional action policies from moments of quantum generative models in Hilbert space via the QuAK algorithm, reporting higher scores and fewer parameters than baselines.
Clear2Fog generates realistic synthetic fog from clear scenes, enabling mixed-density training that outperforms full fixed-density data and improves real-world performance by 1.67 mAP after learning-rate adjustment.
citing papers explorer
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Optical Music Recognition for Real-World Manuscripts with Synthetic Data
Domain adaptation via synthetic manuscript images improves OMR performance on real-world piano manuscripts without requiring in-domain symbols.
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NeuralLVC: Neural Lossless Video Compression via Masked Diffusion with Temporal Conditioning
NeuralLVC achieves better lossless compression than H.264 and H.265 on video sequences by combining masked diffusion with temporal conditioning on frame differences.
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QnRL: Quantum-Native Reinforcement Learning
QnRL is a distributional quantum RL framework that distills conditional action policies from moments of quantum generative models in Hilbert space via the QuAK algorithm, reporting higher scores and fewer parameters than baselines.
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A Data Efficiency Study of Synthetic Fog for Object Detection Using the Clear2Fog Pipeline
Clear2Fog generates realistic synthetic fog from clear scenes, enabling mixed-density training that outperforms full fixed-density data and improves real-world performance by 1.67 mAP after learning-rate adjustment.
- Few-Shot Synthetic Accented Speech for ASR Fine-Tuning: What Helps and When?
- From Dispersion to Attraction: Spectral Dynamics of Hallucination Across Whisper Model Scales