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Found 7 papers, 1 papers with code
Acquiring Dynamic Light Fields through Coded Aperture Camera
A promising solution for compressive light field acquisition is to use a coded aperture camera, with which an entire light field can be computationally reconstructed from several images captured through differently-coded aperture patterns.
Time-Efficient Light-Field Acquisition Using Coded Aperture and Events
Different from the conventional coded-aperture imaging method, our method applies a sequence of coding patterns during a single exposure for an image frame.
Reconstructing Continuous Light Field From Single Coded Image
NeRF-based neural rendering enables high quality view synthesis of a 3-D scene from continuous viewpoints, but when only a single image is given as the input, it struggles to achieve satisfactory quality.
Compressing Sign Information in DCT-based Image Coding via Deep Sign Retrieval
Compressing the sign information of discrete cosine transform (DCT) coefficients is an intractable problem in image coding schemes due to the equiprobable characteristics of the signs.
Acquiring a Dynamic Light Field through a Single-Shot Coded Image
To our knowledge, our method is the first to achieve a finer temporal resolution than the camera itself in compressive light-field acquisition.
Adversarial Patch Attacks on Monocular Depth Estimation Networks
Thanks to the excellent learning capability of deep convolutional neural networks (CNN), monocular depth estimation using CNNs has achieved great success in recent years.
Learning to Capture Light Fields through a Coded Aperture Camera
To make the acquisition process efficient, coded aperture cameras were successfully adopted; using these cameras, a light field is computationally reconstructed from several images that are acquired with different aperture patterns.
