PolarVSR is the first unified architecture for continuous space-time polarization video reconstruction from DoFP captures, using polarization-aware implicit neural representations, a flow-guided variation loss, and a new large-scale benchmark.
Raft: Recurrent all-pairs field transforms for optical flow
2 Pith papers cite this work. Polarity classification is still indexing.
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FCVSR is a frequency-aware deep model for compressed video super-resolution using MGAA and MFFR modules plus contrastive loss, achieving up to 0.14 dB PSNR gain on three public datasets.
citing papers explorer
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PolarVSR: A Unified Framework and Benchmark for Continuous Space-Time Polarization Video Reconstruction
PolarVSR is the first unified architecture for continuous space-time polarization video reconstruction from DoFP captures, using polarization-aware implicit neural representations, a flow-guided variation loss, and a new large-scale benchmark.
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FCVSR: A Frequency-aware Method for Compressed Video Super-Resolution
FCVSR is a frequency-aware deep model for compressed video super-resolution using MGAA and MFFR modules plus contrastive loss, achieving up to 0.14 dB PSNR gain on three public datasets.