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Found 5 papers, 5 papers with code
WaveNet: Wave-Aware Image Enhancement
In this paper, we formulate the enhancement into a signal modulation problem and propose the WaveNet architecture, which performs well in various parameters and improves the feature expression using wave-like feature representation.
Ranked #4 on
Low-Light Image Enhancement
on LOL
Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few Labels
In an effort to further advance semi-supervised generative and classification tasks, we propose a simple yet effective training strategy called dual pseudo training (DPT), built upon strong semi-supervised learners and diffusion models.
Spatial-Temporal Transformer for Video Snapshot Compressive Imaging
In this paper, we consider the reconstruction algorithm in video SCI, i. e., recovering a series of video frames from a compressed measurement.
Deep Generative Modeling on Limited Data with Regularization by Nontransferable Pre-trained Models
Deep generative models (DGMs) are data-eager because learning a complex model on limited data suffers from a large variance and easily overfits.
Spectral Compressive Imaging Reconstruction Using Convolution and Contextual Transformer
Spectral compressive imaging (SCI) is able to encode the high-dimensional hyperspectral image to a 2D measurement, and then uses algorithms to reconstruct the spatio-spectral data-cube.
