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Found 7 papers, 1 papers with code
Enhancing image quality prediction with self-supervised visual masking
Full-reference image quality metrics (FR-IQMs) aim to measure the visual differences between a pair of reference and distorted images, with the goal of accurately predicting human judgments.
Revisiting Image Deblurring with an Efficient ConvNet
In this work, we propose a unified lightweight CNN network that features a large effective receptive field (ERF) and demonstrates comparable or even better performance than Transformers while bearing less computational costs.
Ranked #2 on
Image Defocus Deblurring
on DPD
Video frame interpolation for high dynamic range sequences captured with dual-exposure sensors
Video frame interpolation (VFI) enables many important applications that might involve the temporal domain, such as slow motion playback, or the spatial domain, such as stop motion sequences.
Eikonal Fields for Refractive Novel-View Synthesis
We tackle the problem of generating novel-view images from collections of 2D images showing refractive and reflective objects.
HDR Denoising and Deblurring by Learning Spatio-temporal Distortion Models
Regrettably, capturing DISTORTED sensor readings is time-consuming; as well, there is a lack of CLEAN HDR videos.
X-Fields: Implicit Neural View-, Light- and Time-Image Interpolation
We suggest to represent an X-Field -a set of 2D images taken across different view, time or illumination conditions, i. e., video, light field, reflectance fields or combinations thereof-by learning a neural network (NN) to map their view, time or light coordinates to 2D images.
Neural View-Interpolation for Sparse Light Field Video
We suggest representing light field (LF) videos as "one-off" neural networks (NN), i. e., a learned mapping from view-plus-time coordinates to high-resolution color values, trained on sparse views.
