Seed Optimization with Frozen Generator for Superior Zero-shot Low-light Enhancement

arXiv:2402.09694v1 Announce Type: new
Abstract: In this work, we observe that the generators, which are pre-trained on massive natural images, inherently hold the promising potential for superior low-light image enhancement against varying scenarios.Specifically, we embed a pre-trained generator to Retinex model to produce reflectance maps with enhanced detail and vividness, thereby recovering features degraded by low-light conditions.Taking one step further, we introduce a novel optimization strategy, which backpropagates the gradients to the input seeds rather than the parameters of the …

abstract arxiv cs.cv embed generator generators image images light low maps massive natural observe optimization seed type work zero-shot