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cs.CV2025
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…
cs.CV2025
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.CV2024
Consistency Model is an Effective Posterior Sample Approximation for Diffusion Inverse Solvers
Tongda Xu, Ziran Zhu, Jian Li +8
Diffusion Inverse Solvers (DIS) are designed to sample from the conditional distribution , with a predefined diffusion model , an operator , and a m…