Related papers: Adaptive Depth Imaging with Single-Photon Detector…
Lensless cameras provide a framework to build thin imaging systems by replacing the lens in a conventional camera with an amplitude or phase mask near the sensor. Existing methods for lensless imaging can recover the depth and intensity of…
Highly sensitive photodetectors with single photon level detection is one of the key components to a range of emerging technologies, in particular the ever-growing field of optical communication, remote sensing, and quantum computing.…
Three-dimensional (3D) imaging of thin, extended specimens at nanometer resolution is critical for applications in biology, materials science, advanced synthesis, and manufacturing. One route to 3D imaging is tomography, which requires a…
Images obtained by microscopes are generally degraded by aberrations. Adaptive optics (AO) has been widely used in to compensate for aberrations and improve reduced image quality. Requiring no separate wavefront sensor, sensorless AO…
We report the optical imaging of a single atom with nanometer resolution using an adaptive optical alignment technique that is applicable to general optical microscopy. By decomposing the image of a single laser-cooled atom, we identify and…
Single-photon avalanche diodes (SPADs) are advanced sensors capable of detecting individual photons and recording their arrival times with picosecond resolution using time-correlated Single-Photon Counting detection techniques. They are…
3D photography is a new medium that allows viewers to more fully experience a captured moment. In this work, we refer to a 3D photo as one that displays parallax induced by moving the viewpoint (as opposed to a stereo pair with a fixed…
We present a novel framework to efficiently acquire near-planar anisotropic reflectance in a pixel-independent fashion, using a deep gated mixtureof-experts. While existing work employs a unified network to handle all possible input, our…
Conventional imaging at low light level requires hundreds of detected photons per pixel to suppress the Poisson noise for accurate reflectivity inference. In this letter, we propose a high-efficiency photon-limited imaging technique, called…
In recent years, deep learning methods bring incredible progress to the field of object detection. However, in the field of remote sensing image processing, existing methods neglect the relationship between imaging configuration and…
Monocular depth estimation has been actively studied in fields such as robot vision, autonomous driving, and 3D scene understanding. Given a sequence of color images, unsupervised learning methods based on the framework of…
This paper presents a novel approach to reconstruct complete 3D deformable models over time by a single depth camera. These are the steps employed for deforming objects from single depth camera. The partial surfaces reconstructed from…
Recent years have witnessed the increasing popularity of learning based methods to enhance the color and tone of photos. However, many existing photo enhancement methods either deliver unsatisfactory results or consume too much…
Each image acquisition setup leads to its own camera-specific image characteristics degrading the image quality. In learning-based perception algorithms, characteristics occurring during the application phase, but absent in the training…
This paper presents a new method for 3D depth estimation using the output of an asynchronous time driven image sensor. In association with a high speed Digital Light Processing projection system, our method achieves real-time reconstruction…
We present a novel structured light technique that uses Single Photon Avalanche Diode (SPAD) arrays to enable 3D scanning at high-frame rates and low-light levels. This technique, called "Single-Photon Structured Light", works by sensing…
Recent camera-based 3D object detection is limited by the precision of transforming from image to 3D feature spaces, as well as the accuracy of object localization within the 3D space. This paper aims to address such a fundamental problem…
Reconstructing the 3D shape of an object using several images under different light sources is a very challenging task, especially when realistic assumptions such as light propagation and attenuation, perspective viewing geometry and…
Self-supervised deep learning methods for joint depth and ego-motion estimation can yield accurate trajectories without needing ground-truth training data. However, as they typically use photometric losses, their performance can degrade…
In this paper, we present a new experimental apparatus for the measurement of the detection efficiency of free-space single-photon detectors based on the substitution method. For the first time, we extend the analysis to account for the…