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Found 7 papers, 4 papers with code
Seeing and Hearing: Open-domain Visual-Audio Generation with Diffusion Latent Aligners
Thus, instead of training the giant models from scratch, we propose to bridge the existing strong models with a shared latent representation space.
LDM-ISP: Enhancing Neural ISP for Low Light with Latent Diffusion Models
Specifically, to tailor the pre-trained latent diffusion model to operate on the RAW domain, we train a set of lightweight taming modules to inject the RAW information into the diffusion denoising process via modulating the intermediate features of UNet.
Online Overexposed Pixels Hallucination in Videos with Adaptive Reference Frame Selection
We present a learning-based system to reduce these artifacts without resorting to complex acquisition mechanisms like alternating exposures or costly processing that are typical of high dynamic range (HDR) imaging.
Deep Video Prior for Video Consistency and Propagation
A progressive propagation strategy with pseudo labels is also proposed to enhance DVP's performance on video propagation.
Unsupervised Portrait Shadow Removal via Generative Priors
Qualitative and quantitative experiments on a real-world portrait shadow dataset demonstrate that our approach achieves comparable performance with supervised shadow removal methods.
Invertible Image Signal Processing
Unprocessed RAW data is a highly valuable image format for image editing and computer vision.
Blind Video Temporal Consistency via Deep Video Prior
Extensive quantitative and perceptual experiments show that our approach obtains superior performance than state-of-the-art methods on blind video temporal consistency.
