High diffraction efficiency complex amplitude modulation technique by using antiwave functions.

Complex amplitude modulation (CAM) is a single-step technique that codes the amplitude and phase of a diffracted optical field into a real function. Loading this function onto a phase-only spatial light modulator enables the reconstruction of 3D images. However, the obtained images have poor brightness because of the low diffraction efficiency.

Digital holographic content manipulation for wide-angle holographic near-eye displays.

In recent years, the development of holographic near-eye displays (HNED) has surpassed the progress of digital hologram recording systems, especially in terms of wide-angle viewing capabilities. Thus, there is capture-display parameters incompatibility, which makes it impossible to reconstruct recorded objects in wide-angle display. This paper presents a complete imaging chain extending the available content for wide-angle HNED of pupil and non-pupil configuration with narrow-angle digital holograms of real objects.

Enhancing 3D human pose estimation with NIR single-pixel imaging and time-of-flight technology: a deep learning approach.

The extraction of 3D human pose and body shape details from a single monocular image is a significant challenge in computer vision. Traditional methods use RGB images, but these are constrained by varying lighting and occlusions. However, cutting-edge developments in imaging technologies have introduced new techniques such as single-pixel imaging (SPI) that can surmount these hurdles.

A Study on Generative Models for Visual Recognition of Unknown Scenes Using a Textual Description.

In this study, we investigate the application of generative models to assist artificial agents, such as delivery drones or service robots, in visualising unfamiliar destinations solely based on textual descriptions. We explore the use of generative models, such as Stable Diffusion, and embedding representations, such as CLIP and VisualBERT, to compare generated images obtained from textual descriptions of target scenes with images of those scenes. Our research encompasses three key strategies: image generation, text generation, and text enhancement, the latter involving tools such as ChatGPT to create concise textual descriptions for evaluation.

Deep-learning blurring correction of images obtained from NIR single-pixel imaging.

In challenging scenarios characterized by low-photon conditions or the presence of scattering effects caused by rain, fog, or smoke, conventional silicon-based cameras face limitations in capturing visible images. This often leads to reduced visibility and image contrast. However, using near-infrared (NIR) light within the range of 850-1550 nm offers the advantage of reduced scattering by microparticles, making it an attractive option for imaging in such conditions.