That's What I Said: Fully-Controllable Talking Face Generation

The goal of this paper is to synthesise talking faces with controllable facial motions. To achieve this goal, we propose two key ideas. The first is to establish a canonical space where every face has the same motion patterns but different identities. The second is to navigate a multimodal motion space that only represents motion-related features while eliminating identity information. To disentangle identity and motion, we introduce an orthogonality constraint between the two different latent spaces. From this, our method can generate natural-looking talking faces with fully controllable facial attributes and accurate lip synchronisation. Extensive experiments demonstrate that our method achieves state-of-the-art results in terms of both visual quality and lip-sync score. To the best of our knowledge, we are the first to develop a talking face generation framework that can accurately manifest full target facial motions including lip, head pose, and eye movements in the generated video without any additional supervision beyond RGB video with audio

30 inch Roll-Based Production of High-Quality Graphene Films for Flexible Transparent Electrodes

We report that 30-inch scale multiple roll-to-roll transfer and wet chemical doping considerably enhance the electrical properties of the graphene films grown on roll-type Cu substrates by chemical vapor deposition. The resulting graphene films shows a sheet resistance as low as ~30 Ohm/sq at ~90 % transparency which is superior to commercial transparent electrodes such as indium tin oxides (ITO). The monolayer of graphene shows sheet resistances as low as ~125 Ohm/sq with 97.4% optical transmittance and half-integer quantum Hall effect, indicating the high-quality of these graphene films. As a practical application, we also fabricated a touch screen panel device based on the graphene transparent electrodes, showing extraordinary mechanical and electrical performances

Rapid synthesis of MoS2–Ag nanocomposites via photoreduction for optical tuning and surface-enhanced Raman scattering applications

Semiconductor–metal nanocomposites have been widely investigated to modify the intrinsic properties of materials used for optoelectronic devices and sensing applications. In this study, a method for rapid synthesis of MoS2–Ag nanocomposites via laser-assisted photoreduction was proposed. For the photoreduction process, we used AgNO3 solution as a metal source. Under laser irradiation, Ag ions were easily reduced on MoS2 by photo-generated electrons from MoS2. The optical properties of MoS2–Ag nanocomposites were easily controlled by simple adjustment of the photoreduction time. To investigate the surface-enhanced Raman scattering (SERS) effect of the MoS2–Ag nanocomposites, the SERS spectra of methylene blue (MB) on MoS2–Ag nanocomposites were measured, and the nanocomposites were found to enhance the Raman scattering intensity of MB up to ∼106. Therefore, the laser-assisted photoreduction method has great potential for rapid synthesis and optical tuning of semiconductor–metal nanocomposites

Comparison of Horizontal Accuracy, Shape Similarity and Cost of Three Different Road Mapping Techniques

Accurate spatial information on forest roads is important for forest management and harvest operations. This study evaluated the positional accuracy, shape similarity, and cost of three mapping techniques: GNSS (Global Navigation Satellite System) mapping, CAD file conversion (as-built drawing), and image warping. We chose five road routes within the national forest road system in the Republic of Korea and made digital road maps using each technique. We then compared map accuracy to reference maps made from field surveys. The mapping and field-survey results were compared using point-correspondence, buffering analysis, shape index, and turning function methods. The comparisons indicate that GNSS mapping is the best technique because it generated the highest accuracy (Root Mean Square Error: GNSS mapping 1.28, image warping 7.13, CAD file conversion 13.35), the narrowest buffering width for 95% of the routes overlapped (buffering width: GNSS mapping 1.5 m, image warping 18 m, CAD file conversion 24 m), highest shape similarity (shape index: GNSS mapping 19.6–28.9, image warping 7.2–10.8, CAD file conversion 6.5–7.4), and smallest area size difference in turning function analysis (GNSS mapping 2814–4949, image warping 7972–26,256, CAD file conversion 8661–27,845). However, GNSS requires more time (236 min/km) and costs more ($139.64/km) to produce a digital road map as compared to CAD file conversion (99 min/km and$40.90/km) and image warping (180 min/km and $81.84/km). Managers must decide on the trade-off between accuracy and cost while considering the demand and purpose of maps. GNSS mapping can be used for small-scale mapping or short-haul routes that require a small error range. Image warping was the lowest cost and produced low-accuracy maps, but may be suitable for large-scale mapping at the regional or national level. CAD file conversion was expected to be the most accurate method, because it converted as-built drawings to a map. However, we found that it was the least accurate method, indicating low accuracy of the as-built drawings. Efforts should be made to improve the accuracy of the as-built drawings in Korea

Application of Viewshed and Spatial Aesthetic Analyses to Forest Practices for Mountain Scenery Improvement in the Republic of Korea

Forest practices for mountainous areas can enhance the scenery value and function of forests. However, forest scenery management is rarely implemented except for conservation areas and public forests. In this study, we first used the viewshed analysis to extract visible and invisible zones from the surface areas of ordinary mountains in Korea, and then we used spatial aesthetic analysis to interpret the human-recognized characteristics on the visible zones of mountain scenery. Finally, based on the results of both analyses, reasonable guidelines for forest practice planning were proposed to improve the scenery of ordinary mountains. The result shows that the viewshed analysis made it possible to extract visible and invisible areas from the surface areas of ordinary mountains, and to determine the scale of zoning for forest practices to improve mountain scenery. In addition, using spatial aesthetic analysis, it was possible to explain the characteristics of mountain scenery according to distance and elevational differences between viewpoint and target, and to suggest a treatment target and direction for forest practices to improve the mountain scenery. This study is meaningful in that the viewshed and spatial aesthetic analyses were applied to evaluate the current scenery of ordinary mountains and to present guidelines for forest practice planning to promote their own scenery values

Empirical Comparison of Supervised Learning Methods for Assessing the Stability of Slopes Adjacent to Military Operation Roads

The Civilian Access Control Zone (CACZ), south of the Demilitarized Zone (DMZ) separating North and South Korea, has functioned as a unique bio-reserve owing to restrictions on human use. However, it is now increasingly threatened by damaged land and slope failures. In this study, a machine-learning-based method was used to assess slope stability by introducing the random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost), and logistic regression (LR) approaches. These classification models were trained and evaluated on 393 slope stability cases from 2009 to 2019 to assess slope stability in the northern area of the Civilian Control Line, South Korea. For comparison, the performance of these classification models was measured by considering the accuracy, Cohen’s kappa, F1-score, recall rate, precision, and area under the ROC curve (AUC). Furthermore, 14 influencing factors (slope, vegetation, structure conditions, etc.) were considered to explore feature importance. The evaluation and comparison of the results showed that the performance of all classifier models was satisfactory for assessing the stability of the slope, the ability of LR was validated (accuracy = 0.847; AUC = 0.838), and XGBoost proved to be the most efficient method for predicting slope stability (accuracy = 0.903; AUC = 0.900). Among the 14 influencing factors, the external condition was the most important. The proposed supervised learning method offers a promising method for assessing slope status, may be beneficial for government agencies in early-stage risk mitigation, and provides a database for efficient restoration management

Real-Time Optical Visualization of Graphene Defects and Grain Boundaries by the Thermal Oxidation of a Graphene-Coated Copper Foil

We have constructed a system that can visualize graphene defects in real time by coupling a heater and an optical instrument. In this system, the phenomenon of copper oxidation was used to visualize defects in graphene. When heat is applied to graphene synthesized on a copper foil, oxygen in the atmosphere penetrates through the graphene grain boundaries and oxidizes the copper substrate. This system observes the entire process of copper oxidation in real time and controls the rate of the visualization process by adjusting the temperature and time. A temperature–time graph for graphene defect visualization was plotted based on the experimental data, which indicates that it only requires 5 min at 225 °C for completion of the visualization process. Additionally, through scanning electron microscopy–energy-dispersive X-ray spectroscopy and X-ray photoelectron spectroscopy analyses, it has been confirmed that copper oxidation occurs during the process of visualization of graphene defects. Compared to conventional optical visualization methods, this technique is faster and more convenient. This system is expected to enable easy and fast quality inspection for the mass production of graphene

Real-Time Optical Visualization of Graphene Defects and Grain Boundaries by the Thermal Oxidation of a Graphene-Coated Copper Foil

We have constructed a system that can visualize graphene defects in real time by coupling a heater and an optical instrument. In this system, the phenomenon of copper oxidation was used to visualize defects in graphene. When heat is applied to graphene synthesized on a copper foil, oxygen in the atmosphere penetrates through the graphene grain boundaries and oxidizes the copper substrate. This system observes the entire process of copper oxidation in real time and controls the rate of the visualization process by adjusting the temperature and time. A temperature–time graph for graphene defect visualization was plotted based on the experimental data, which indicates that it only requires 5 min at 225 °C for completion of the visualization process. Additionally, through scanning electron microscopy–energy-dispersive X-ray spectroscopy and X-ray photoelectron spectroscopy analyses, it has been confirmed that copper oxidation occurs during the process of visualization of graphene defects. Compared to conventional optical visualization methods, this technique is faster and more convenient. This system is expected to enable easy and fast quality inspection for the mass production of graphene