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Found 3 papers, 0 papers with code
Lightweight Image Enhancement Network for Mobile Devices Using Self-Feature Extraction and Dense Modulation
The proposed network include self-feature extraction module which produces modulation parameters from low-quality image itself, and provides them to modulate the features in the network.
Smoother Network Tuning and Interpolation for Continuous-level Image Processing
Extensive results for various image processing tasks indicate that the performance of FTN is comparable in multiple continuous levels, and is significantly smoother and lighter than that of other frameworks.
Regularized Adaptation for Stable and Efficient Continuous-Level Learning on Image Processing Networks
In this paper, we propose a novel continuous-level learning framework using a Filter Transition Network (FTN) which is a non-linear module that easily adapt to new levels, and is regularized to prevent undesirable side-effects.
