Recurrent Dynamic Range Extension
We present an approach to progressively extend the highlights of an image. Instead of reconstructing the full dynamic range of a complex scene directly, we learn a simpler task first: We extend the dynamic range of an input image by a single exposure value. Once this is mastered, we retrieve the full HDR image for the scene by executing our network recurrently, progressively increasing the dynamic range of the input. Our formulation is agnostic to the input dynamic range and targets a bounded output domain. This enables us to use widely available RAW images for the reconstruction task and adapt adversarial losses to construct realistic images. By incorporating Memory Replay for backpropag...
| Authors | Sebastian Dille, Keru Fu, S. Mahdi H. Miangoleh et al. |
|---|---|
| Primary category | eess.IV |
| Published | 11 September 2026 |
| Last updated at source | 11 September 2026 |
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