Search Results for author:
Found 9 papers, 3 papers with code
Spatially Varying Nanophotonic Neural Networks
The explosive growth of computation and energy cost of artificial intelligence has spurred strong interests in new computing modalities as potential alternatives to conventional electronic processors.
Thin On-Sensor Nanophotonic Array Cameras
The optical array is embedded on a metasurface that, at 700~nm height, is flat and sits on the sensor cover glass at 2. 5~mm focal distance from the sensor.
Stochastic Light Field Holography
The Visual Turing Test is the ultimate goal to evaluate the realism of holographic displays.
Seeing With Sound: Long-range Acoustic Beamforming for Multimodal Scene Understanding
We validate the benefit of adding sound detections to existing RGB cameras in challenging automotive scenarios, where camera-only approaches fail or do not deliver the ultra-fast rates of pressure sensors.
OmniHorizon: In-the-Wild Outdoors Depth and Normal Estimation from Synthetic Omnidirectional Dataset
Finally, we demonstrate in-the-wild depth and normal estimation on real-world images with UBotNet trained purely on our OmniHorizon dataset, showing the promise of proposed dataset and network for scene understanding.
ChromaCorrect: Prescription Correction in Virtual Reality Headsets through Perceptual Guidance
In this work, we remedy the usage of prescription eyeglasses in Virtual Reality (VR) headsets by shifting the optical complexity completely into software and propose a prescription-aware rendering approach for providing sharper and immersive VR imagery.
Neural Étendue Expander for Ultra-Wide-Angle High-Fidelity Holographic Display
As a result, modern holographic displays possess low \'{e}tendue, which is the product of the display area and the maximum solid angle of diffracted light.
FoV-NeRF: Foveated Neural Radiance Fields for Virtual Reality
To tackle these problems toward six-degrees-of-freedom, egocentric, and stereo NeRF in VR, we present the first gaze-contingent 3D neural representation and view synthesis method.
DeepCGH: 3D computer-generated holography using deep learning
The goal of computer-generated holography (CGH) is to synthesize custom illu- mination patterns by modulating a coherent light beam.
