UpCycling: Semi-supervised 3D Object Detection without Sharing Raw-level Unlabeled Scenes

Semi-supervised Learning (SSL) has received increasing attention in autonomous driving to relieve enormous burden for 3D annotation. In this paper, we propose UpCycling, a novel SSL framework for 3D object detection with zero additional raw-level point cloud: learning from unlabeled de-identified intermediate features (i.e., smashed data) for privacy preservation. The intermediate features do not require additional computation on autonomous vehicles since they are naturally produced by the inference pipeline. However, augmenting 3D scenes at a feature level turns out to be a critical issue: applying the augmentation methods in the latest semi-supervised 3D object detectors distorts intermediate features, which causes the pseudo-labels to suffer from significant noise. To solve the distortion problem while achieving highly effective SSL, we introduce hybrid pseudo labels, feature-level Ground Truth sampling (F-GT) and Rotation (F-RoT), which safely augment unlabeled multi-type 3D scene features and provide high-quality supervision. We implement UpCycling on two representative 3D object detection models, SECOND-IoU and PV-RCNN, and perform experiments on widely-used datasets (Waymo, KITTI, and Lyft). While preserving privacy with zero raw-point scene, UpCycling significantly outperforms the state-of-the-art SSL methods that utilize raw-point scenes, in both domain adaptation and partial-label scenarios

BroadBEV: Collaborative LiDAR-camera Fusion for Broad-sighted Bird's Eye View Map Construction

A recent sensor fusion in a Bird's Eye View (BEV) space has shown its utility in various tasks such as 3D detection, map segmentation, etc. However, the approach struggles with inaccurate camera BEV estimation, and a perception of distant areas due to the sparsity of LiDAR points. In this paper, we propose a broad BEV fusion (BroadBEV) that addresses the problems with a spatial synchronization approach of cross-modality. Our strategy aims to enhance camera BEV estimation for a broad-sighted perception while simultaneously improving the completion of LiDAR's sparsity in the entire BEV space. Toward that end, we devise Point-scattering that scatters LiDAR BEV distribution to camera depth distribution. The method boosts the learning of depth estimation of the camera branch and induces accurate location of dense camera features in BEV space. For an effective BEV fusion between the spatially synchronized features, we suggest ColFusion that applies self-attention weights of LiDAR and camera BEV features to each other. Our extensive experiments demonstrate that BroadBEV provides a broad-sighted BEV perception with remarkable performance gains

Seoul Hope Plus Savings Accounts: Asset-Building Program for Low-Income Households in Seoul

Seoul Hope Plus Savings Accounts: Asset-Building Program for Low-Income Households in Seou

Evaluation of Two Approaches for Aligning Data Obtained from a Motion Capture System and an In-Shoe Pressure Measurement System

An in-shoe pressure measurement (IPM) system can be used to measure center of pressure (COP) locations, and has fewer restrictions compared to the more conventional approach using a force platform. The insole of an IPM system, however, has its own coordinate system. To use an IPM system along with a motion capture system, there is thus a need to align the coordinate systems of the two measurement systems. To address this need, the current study examined two different approaches—rigid body transformation and nonlinear mapping (i.e., multilayer feed-forward neural network (MFNN))—to express COP measurements from an IPM system in the coordinate system of a motion capture system. Ten participants (five male and five female) completed several simulated manual material handling (MMH) activities, and during these activities the performance of the two approaches was assessed. Results indicated that: (1) performance varied between MMH activity types; and (2) a MFNN performed better than or comparable to the rigid body transformation, depending on the specific input variable sets used. Further, based on the results obtained, it was argued that a nonlinear mapping vs. rigid body transformation approach may be more effective to account for shoe deformation during MMH or potentially other types of physical activity

A comparative study of wooden house construction in Jeollanamdo in South Korea and Okinawa Prefecture in Japan following World War II

This paper compares the changes in the production of wooden houses after WWII in Jeollanamdo in South Korea and Okinawa Prefecture in Japan. This study finds that wooden house production shares the following similarities in both locations: (1) traditional wooden post and beam houses were constructed by local carpenters using local wood; (2) following WWII, houses came to be constructed of concrete blocks or reinforced concrete instead of wood; (3) in the 1980s and the 1990s, the number of light-frame wood houses increased; and (4) in the 1990s and the 2000s, wooden post and beam houses increased. This paper examines two case studies conducted in Jeollanamdo and Okinawa Prefecture, respectively, to better understand the current status of wooden post and beam house construction. Jeollanamdo initiated a Happiness Village Project in 2007. This initiative increased the construction of post and beam houses by addressing the shortage of experienced contractors. Starting in the 1990s in Okinawa, the adoption of precut lumber increased the construction post and beam houses, negating the need for traditionally skilled carpenters. However, due to there being few experienced contractors, factories producing precut lumber supported small-scale contractors through training and additional services. Chemical modification of respiratory complex I. The author focuses on structural features of the binding pocket of quinone/inhibitors in complex I

Unravelling ionic speciation and hydration structure of Fe(III/II) redox couples for thermoelectrochemical cells

Thermoelectrochemical cells (TECs) are promising devices for harvesting heat waste, but their widespread use has been hindered by their low thermopower densities. High-power TECs require an electrolyte solution that exhibits both high Seebeck coefficient (Se) and high ionic conductivity; thus far, this has been a challenge. Recently, we demonstrated that proper selection of the counter anion of Fe(III)/(II) salts can resolve the aforementioned issue, that n-type (positive Se) TECs employing the Fe(III)/(II) perchlorate redox couple display unprecedented high areal power densities compared to TECs employing Fe(III)/(II) chloride or Fe(III)/(II) sulfate couple. Herein, we unravel that the excellent performance of the Fe(III)/(II) perchlorate is ascribed to the non-coordinating nature of its perchlorate anion, which suppresses the formation of the ion pairs that reduce the Se and ionic conductivity. UV–Vis and dielectric relaxation analysis revealed that the redox reaction of the hexa aquo complexes (Fe(H2O)6 3+/2+), formed Fe(III)/(II) perchlorate, is accompanied by a hydration-number change larger than those of anion-coordinated species, which are dominant in chloride or sulfate media. In addition, n-type TECs can be combined in-series with p-type (negative Se) TECs to provide output powers high enough for practical application. © 2020 Elsevier Ltd1

Ultra-compact terahertz 50:50 power splitter designed by a perceptron based algorithm

We designed and simulated an ultra-compact 1 × 2 power splitter operating in the terahertz region. A machine learning approach was implemented to design the photonic device. The designed power splitter has a footprint of 500 µm × 500 µm. We calculated the insertion loss using a three-dimensional finite difference time domain method. The calculated insertion loss was less than 4 dB over the operating wavelength range of 275–325 µm. The machine learning algorithm implemented in this work can be applied to the inverse design of various photonic devices.11

Efficient Content Verification in Named Data Networking

ABSTRACT In Named Data Networking, contents are retrieved from network caches as well as the content server by their name. This aspect arises severe security concerns on content integrity. Especially, if poisoned contents lie in the network cache, called content store(CS), interests would be served by the poisoned content rather than they propagate toward the content server. Consequently, users whose interests pass through the contaminated CS cannot access the valid content. In order to resolve the problem, every content is verified before they are inserted into the CS. However, this builtin verification mechanism is not practically feasible due to its huge computational overhead. In this paper, we address problems of content integrity in NDN in details, including how to violate content integrity. We also propose a practical solution that efficiently detects poisoned contents from the CS with minimum overhead. Since the proposed scheme aligns to the basic NDN architecture, it is a practical and effective solution