Driving Scene Perception Network: Real-time Joint Detection, Depth Estimation and Semantic Segmentation

As the demand for enabling high-level autonomous driving has increased in recent years and visual perception is one of the critical features to enable fully autonomous driving, in this paper, we introduce an efficient approach for simultaneous object detection, depth estimation and pixel-level semantic segmentation using a shared convolutional architecture. The proposed network model, which we named Driving Scene Perception Network (DSPNet), uses multi-level feature maps and multi-task learning to improve the accuracy and efficiency of object detection, depth estimation and image segmentation tasks from a single input image. Hence, the resulting network model uses less than 850 MiB of GPU memory and achieves 14.0 fps on NVIDIA GeForce GTX 1080 with a 1024x512 input image, and both precision and efficiency have been improved over combination of single tasks.Comment: 9 pages, 7 figures, WACV'1

Modeling secondary organic aerosol formation from biogenic hydrocarbons

Secondary organic aerosol (SOA) is formed generally by the oxidation of gas-phase volatile organic compounds (VOCs) to form semi- or non-volatile products that then undergo gas to particle partitioning. In this work, the Caltech Atmospheric Chemistry Mechanism (CACM) and the Model to Predict the Multi-phase Partitioning of Organics (MPMPO) were updated with detailed chemistry associated with three monoterpene species---alpha-pinene, beta-pinene, and d-limonene. The updated CACM and MPMPO modules were calibrated by ozone formation and SOA yield data for alpha-pinene, beta-pinene, and d-limonene from chamber experiments. Then, the updated CACM and MPMPO were incorporated into the Community Multi-scale Air Quality Model v4.4 (CMAQ). CMAQ with the updated CACM and MPMPO was applied to the eastern United States (US) for August 3-4, 2004. It was found that SOA formation for this domain was dominated by monoterpenes. CMAQ with CACM and MPMPO predicted similar SOA formation when compared to CMAQ with the CB-IV gas-phase mechanism and the SORGAM SOA module. However, responses of SOA predictions at Thompson Farm, New Hampshire to domain NO, emissions changes and temperature variations are different for CACM/MPMPO and CB-IV/SORGAM. In addition, an aqueous-phase chemistry mechanism (AgChem) was developed to study the potential of SOA formation via irreversible cloud processing of organic compounds. AgChem considers irreversible organic reactions that lead mainly to the formation of carboxylic acids, which are usually less volatile than the corresponding aldehydes. AgChem was incorporated into CMAQ with CACM/MPMPO and applied to the eastern US for August 3-4, 2004. The CMAQ simulation indicates that the maximum contribution of SOA formation from irreversible reactions of organics in clouds is 0.28 mug/m3 for 24-hour average concentrations and 0.60 mug/m3 for one-hour average concentrations at certain locations. On average, domain-wide surface SOA predictions over the episode are increased by 8.6% when irreversible, in-cloud processing of organics is considered. For our modeling domain and episode, the increase of SOA predictions is due to the cloud processing of oxidation products from monoterpenes, while contribution from irreversible cloud processing of isoprene oxidation products is negligible

Metal-Free Flat Lens Using Negative Refraction by Nonlinear Four-wave Mixing

A perfect lens with unlimited resolution has always posed a challenge to both theoretical and experimental physicists. Recent developments in optical meta-materials promise an attractive approach towards perfect lenses using negative refraction to overcome the diffraction limit, improving resolution. However, those artificially engineered meta-materials usually company by high losses from metals and are extremely difficult to fabricate. An alternative proposal using negative refraction by four-wave mixing has attracted much interests recently, though most of existing experiments still require metals and none of them has been implemented for an optical lens. Here we experimentally demonstrate a metal-free flat lens for the first time using negative refraction by degenerate four-wave mixing with a thin glass slide. We realize optical lensing effect utilizing a nonlinear refraction law, which may have potential applications in microscopy