3 papers
cs.CV2026
Versatile Recompression-Aware Perceptual Image Super-Resolution
Mingwei He, Tongda Xu, Xingtong Ge +3
Perceptual image super-resolution (SR) methods restore degraded images and produce sharp outputs. In practice, those outputs are usually recompressed for storage and transmission.…
cs.CV2026
Rethinking Test Time Scaling for Flow-Matching Generative Models
Qingtao Yu, Changlin Song, Minghao Sun +6
The performance of text-to-image diffusion models may be improved at test-time by scaling computation to search for a generated image that maximizes a given reward function. While…
math-ph2025
Operator-Consistent Physics-Informed Learning for Wafer Thermal Reconstruction in Lithography
Ze Tao, Fujun Liu, Yuxi Jin +6
Thermal field reconstruction in post-exposure bake (PEB) is critical for advanced lithography, yet current physics-informed neural networks (PINNs) suffer from inconsistent accurac…