Frame interpolation is an essential video processing technique that adjusts the temporal resolution of an image sequence.
Modern smartphones can continuously stream multi-megapixel RGB images at 60Hz, synchronized with high-quality 3D pose information and low-resolution LiDAR-driven depth estimates.
We use data captured with a consumer smartphone camera to demonstrate that, after a one-time calibration step, our approach improves upon prior works for both defocus map estimation and blur removal, despite being entirely unsupervised.
Virtual Reality (VR) has shown great potential to revolutionize the market by providing users immersive experiences with freedom of movement.
Networking and Internet Architecture
When a camera is pointed at a strong light source, the resulting photograph may contain lens flare artifacts.
We present a novel algorithm for transferring artistic styles of semantically meaningful local regions of an image onto local regions of a target video while preserving its photorealism.
Photorealistic style transfer is the task of transferring the artistic style of an image onto a content target, producing a result that is plausibly taken with a camera.
In this work, we present a camera configuration for acquiring "stereoscopic dark flash" images: a simultaneous stereo pair in which one camera is a conventional RGB sensor, but the other camera is sensitive to near-infrared and near-ultraviolet instead of R and B.
We present a method for precisely time-synchronizing the capture of image sequences from a collection of smartphone cameras connected over WiFi.
Machine learning techniques work best when the data used for training resembles the data used for evaluation.
Ranked #1 on Color Image Denoising on Darmstadt Noise Dataset
We present a technique for jointly denoising bursts of images taken from a handheld camera.
For this, we introduce a new neural network architecture inspired by bilateral grid processing and local affine color transforms.