arXiv AI By Samira Malek, Haichuan Zhang, Chul Lee, Vishal Monga

Leveraging Phase Information to Boost Unrolled Network Learning for Image Deblurring

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arXiv:2607. 00251v1 Announce Type: cross Abstract: While most image deblurring techniques directly restore the spatial image variable, we propose an amplitude and phase decomposition recognizing the importance of accurate phase estimation in recovering sharp image details.

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arXiv AI
1d ago

PickMoment: Continuous-Time Single-Image-to-Video via Learning Deblurring and Blur-to-Video

PickMoment is a continuous‑time model that learns to predict the interval‑mean blur over arbitrary sub‑intervals of a camera exposure, unifying single‑image deblurring, blur‑to‑video generation, and continuous‑time pick‑a‑moment recovery. It is trained with three supervisions derived from the blur integral: an empirical reconstruction loss, an additivity loss for self‑consistency, and a sharp‑frame loss at zero interval. The model achieves state‑of‑the‑art performance on GoPro and HIDE for generative deblurring, competitive results on RealBlur, and the highest per‑frame fidelity on GoPro‑7 blur‑to‑video, all in a single forward pass.

By Junseong Shin, Hyeonsu Jo, Daehyun Kim, Tae Hyun Kim