arXiv subjects

Taewoo Kim

Publications and source records attributed to Taewoo Kim.

At least 37 records · Page 2Linked to original sources

arXiv2023

The Seoul National University AGN Monitoring Project IV: H$α$ reverberation mapping of 6 AGNs and the H$α$ Size-Luminosity Relation

The broad line region (BLR) size-luminosity relation has paramount importance for estimating the mass of black holes in active galactic nuclei (AGNs). Traditionally, the size of the H$β$ BLR is often estimated from the optical continuum luminosity at 5100\angstrom{} , while the size of the H$α$ BLR and its correlation with the luminosity is much less constrained. As a part of the Seoul National University AGN Monitoring Project (SAMP) which provides six-year photometric and spectroscopic monitoring data, we present our measurements of the H$α$ lags of 6 high-luminosity AGNs. Combined with the measurements for 42 AGNs from the literature, we derive the size-luminosity relations of H$α$ BLR against broad H$α$ and 5100\angstrom{} continuum luminosities. We find the slope of the relations to be $0.61\pm0.04$ and $0.59\pm0.04$, respectively, which are consistent with the \hb{} size-luminosity relation. Moreover, we find a linear relation between the 5100\angstrom{} continuum luminosity and the broad H$α$ luminosity across 7 orders of magnitude. Using these results, we propose a new virial mass estimator based on the H$α$ broad emission line, finding that the previous mass estimates based on the scaling relations in the literature are overestimated by up to 0.7 dex at masses lower than $10^7$~M$_{\odot}$.

astro-ph.GA↗

arXiv2023

RobustSwap: A Simple yet Robust Face Swapping Model against Attribute Leakage

Face swapping aims at injecting a source image's identity (i.e., facial features) into a target image, while strictly preserving the target's attributes, which are irrelevant to identity. However, we observed that previous approaches still suffer from source attribute leakage, where the source image's attributes interfere with the target image's. In this paper, we analyze the latent space of StyleGAN and find the adequate combination of the latents geared for face swapping task. Based on the findings, we develop a simple yet robust face swapping model, RobustSwap, which is resistant to the potential source attribute leakage. Moreover, we exploit the coordination of 3DMM's implicit and explicit information as a guidance to incorporate the structure of the source image and the precise pose of the target image. Despite our method solely utilizing an image dataset without identity labels for training, our model has the capability to generate high-fidelity and temporally consistent videos. Through extensive qualitative and quantitative evaluations, we demonstrate that our method shows significant improvements compared with the previous face swapping models in synthesizing both images and videos. Project page is available at https://robustswap.github.io/

cs.CV↗

arXiv2023

The Early Light Curve of a Type Ia Supernova 2021hpr in NGC 3147: Progenitor Constraints with the Companion Interaction Model

The progenitor system of Type Ia supernovae (SNe Ia) is expected to be a close binary system of a carbon/oxygen white dwarf (WD) and a non-degenerate star or another WD. Here, we present results from a high-cadence monitoring observation of SN 2021hpr in a spiral galaxy, NGC 3147, and constraints on the progenitor system based on its early multi-color light curve data. First, we classify SN 2021hpr as a normal SN Ia from its long-term photometric and spectroscopic data. More interestingly, we found a significant "early excess" in the light curve over a simple power-law $\sim t^{2}$ evolution. The early light curve evolves from blue to red and blue during the first week. To explain this, we fitted the early part of $BVRI$-band light curves with a two-component model of the ejecta-companion interaction and a simple power-law model. The early excess and its color can be explained by shock cooling emission due to a companion star having a radius of $8.84\pm0.58$$R_{\odot}$. We also examined HST pre-explosion images with no detection of a progenitor candidate, consistent with the above result. However, we could not detect signs of a significant amount of the stripped mass from a non-degenerate companion star ($\lesssim0.003\,M_{\odot}$ for H$α$ emission). The early excess light in the multi-band light curve supports a non-degenerate companion in the progenitor system of SN 2021hpr. At the same time, the non-detection of emission lines opens a door for other methods to explain this event.

astro-ph.SR↗

arXiv2022

Self-Driving like a Human driver instead of a Robocar: Personalized comfortable driving experience for autonomous vehicles

This paper issues an integrated control system of self-driving autonomous vehicles based on the personal driving preference to provide personalized comfortable driving experience to autonomous vehicle users. We propose an Occupant's Preference Metric (OPM) which is defining a preferred lateral and longitudinal acceleration region with maximum allowable jerk for users. Moreover, we propose a vehicle controller based on control parameters enabling integrated lateral and longitudinal control via preference-aware maneuvering of autonomous vehicles. The proposed system not only provides the criteria for the occupant's driving preference, but also provides a personalized autonomous self-driving style like a human driver instead of a Robocar. The simulation and experimental results demonstrated that the proposed system can maneuver the self-driving vehicle like a human driver by tracking the specified criterion of admissible acceleration and jerk.

eess.SY↗

arXiv2022

Rationale-aware Autonomous Driving Policy utilizing Safety Force Field implemented on CARLA Simulator

Despite the rapid improvement of autonomous driving technology in recent years, automotive manufacturers must resolve liability issues to commercialize autonomous passenger car of SAE J3016 Level 3 or higher. To cope with the product liability law, manufacturers develop autonomous driving systems in compliance with international standards for safety such as ISO 26262 and ISO 21448. Concerning the safety of the intended functionality (SOTIF) requirement in ISO 26262, the driving policy recommends providing an explicit rational basis for maneuver decisions. In this case, mathematical models such as Safety Force Field (SFF) and Responsibility-Sensitive Safety (RSS) which have interpretability on decision, may be suitable. In this work, we implement SFF from scratch to substitute the undisclosed NVIDIA's source code and integrate it with CARLA open-source simulator. Using SFF and CARLA, we present a predictor for claimed sets of vehicles, and based on the predictor, propose an integrated driving policy that consistently operates regardless of safety conditions it encounters while passing through dynamic traffic. The policy does not have a separate plan for each condition, but using safety potential, it aims human-like driving blended in with traffic flow.

cs.RO↗

arXiv2022

Style Your Hair: Latent Optimization for Pose-Invariant Hairstyle Transfer via Local-Style-Aware Hair Alignment

Editing hairstyle is unique and challenging due to the complexity and delicacy of hairstyle. Although recent approaches significantly improved the hair details, these models often produce undesirable outputs when a pose of a source image is considerably different from that of a target hair image, limiting their real-world applications. HairFIT, a pose-invariant hairstyle transfer model, alleviates this limitation yet still shows unsatisfactory quality in preserving delicate hair textures. To solve these limitations, we propose a high-performing pose-invariant hairstyle transfer model equipped with latent optimization and a newly presented local-style-matching loss. In the StyleGAN2 latent space, we first explore a pose-aligned latent code of a target hair with the detailed textures preserved based on local style matching. Then, our model inpaints the occlusions of the source considering the aligned target hair and blends both images to produce a final output. The experimental results demonstrate that our model has strengths in transferring a hairstyle under larger pose differences and preserving local hairstyle textures.

cs.CV↗

arXiv2022

Event-guided Deblurring of Unknown Exposure Time Videos

Motion deblurring is a highly ill-posed problem due to the loss of motion information in the blur degradation process. Since event cameras can capture apparent motion with a high temporal resolution, several attempts have explored the potential of events for guiding deblurring. These methods generally assume that the exposure time is the same as the reciprocal of the video frame rate. However, this is not true in real situations, and the exposure time might be unknown and dynamically varies depending on the video shooting environment(e.g., illumination condition). In this paper, we address the event-guided motion deblurring assuming dynamically variable unknown exposure time of the frame-based camera. To this end, we first derive a new formulation for event-guided motion deblurring by considering the exposure and readout time in the video frame acquisition process. We then propose a novel end-to-end learning framework for event-guided motion deblurring. In particular, we design a novel Exposure Time-based Event Selection(ETES) module to selectively use event features by estimating the cross-modal correlation between the features from blurred frames and the events. Moreover, we propose a feature fusion module to fuse the selected features from events and blur frames effectively. We conduct extensive experiments on various datasets and demonstrate that our method achieves state-of-the-art performance.

cs.CV↗

arXiv2022

HairFIT: Pose-Invariant Hairstyle Transfer via Flow-based Hair Alignment and Semantic-Region-Aware Inpainting

Hairstyle transfer is the task of modifying a source hairstyle to a target one. Although recent hairstyle transfer models can reflect the delicate features of hairstyles, they still have two major limitations. First, the existing methods fail to transfer hairstyles when a source and a target image have different poses (e.g., viewing direction or face size), which is prevalent in the real world. Also, the previous models generate unrealistic images when there is a non-trivial amount of regions in the source image occluded by its original hair. When modifying long hair to short hair, shoulders or backgrounds occluded by the long hair need to be inpainted. To address these issues, we propose a novel framework for pose-invariant hairstyle transfer, HairFIT. Our model consists of two stages: 1) flow-based hair alignment and 2) hair synthesis. In the hair alignment stage, we leverage a keypoint-based optical flow estimator to align a target hairstyle with a source pose. Then, we generate a final hairstyle-transferred image in the hair synthesis stage based on Semantic-region-aware Inpainting Mask (SIM) estimator. Our SIM estimator divides the occluded regions in the source image into different semantic regions to reflect their distinct features during the inpainting. To demonstrate the effectiveness of our model, we conduct quantitative and qualitative evaluations using multi-view datasets, K-hairstyle and VoxCeleb. The results indicate that HairFIT achieves a state-of-the-art performance by successfully transferring hairstyles between images of different poses, which has never been achieved before.

cs.CV↗

arXiv2021

Electrochemical Screening of Contact Layers for Metal Halide Perovskites

Optimizing selective contact layers in photovoltaics is necessary to yield high performing stable devices. However, this has been difficult for perovskites due to their complex interfacial defects that affect carrier concentrations in the active layer as well as charge transfer and recombination at the interface. Using vacuum thermally-evaporated tin oxide as a case study, we highlight electrochemical tests that are simple yet screen device-relevant contact layer properties, making them useful for process development and quality control. Specifically, we show that cyclic voltammetry and potentiostatic chronoamperometry correlate to key performance parameters in completed devices as well as other material/interfacial properties relevant to devices such as shunt pathways and chemical composition. Having fast, reliable, scalable, and actionable probes of electronic properties is increasingly important as halide perovskite photovoltaics approach their theoretical limits and scale to large-area devices.

cond-mat.mtrl-sci↗

arXiv2021

Search of Intermediate Mass Black Holes at Low Redshift with Intra-night Variability

We present a sample of intermediate-mass black hole (IMBH) candidates based on the detection of a broad H$α$ emission line and variability, which are selected from the Sloan Digital Sky Survey Data Release 7. By performing spectral decomposition of emission lines as well as visual inspection, we initially identified 131 targets with a broad H$α$ line among a large sample of emission-line galaxies. We further selected 25 IMBH candidates, whose estimated black hole mass (M$_{\rm BH}$) is less than $10^6 \rm M_{\odot}$. To constrain the nature of these candidates, we analyzed X-ray properties and performed an intra-night variability monitoring with optical telescopes. Based on the optical variability analysis, we report a sample of 11 targets with detected intra-night variability as the best IMBH candidates, which are suitable for follow-up observations for accurate M$_{\rm BH}$ determination such as reverberation mapping campaigns.

astro-ph.GA↗

arXiv2021

K-Hairstyle: A Large-scale Korean Hairstyle Dataset for Virtual Hair Editing and Hairstyle Classification

The hair and beauty industry is a fast-growing industry. This led to the development of various applications, such as virtual hair dyeing or hairstyle transfer, to satisfy the customer's needs. Although several hairstyle datasets are available for these applications, they often consist of a relatively small number of images with low resolution, thus limiting their performance on high-quality hair editing. In response, we introduce a novel large-scale Korean hairstyle dataset, K-hairstyle, containing 500,000 high-resolution images. In addition, K-hairstyle includes various hair attributes annotated by Korean expert hairstylists as well as hair segmentation masks. We validate the effectiveness of our dataset via several applications, such as hair dyeing, hairstyle transfer, and hairstyle classification. K-hairstyle is publicly available at https://psh01087.github.io/K-Hairstyle/.

cs.CV↗

arXiv2021

H$α$ Reverberation Mapping of the Intermediate-Mass Active Galactic Nucleus in NGC 4395

We present the results of a high-cadence spectroscopic and imaging monitoring campaign of the active galactic nucleus (AGN) of NGC 4395. High signal-to-noise-ratio spectra were obtained at the Gemini-N 8 m telescope using the GMOS integral field spectrograph (IFS) on 2019 March 7, and at the Keck-I 10 m telescope using the Low-Resolution Imaging Spectrometer (LRIS) with slitmasks on 2019 March 3 and April 2. Photometric data were obtained with a number of 1 m-class telescopes during the same nights. The narrow-line region (NLR) is spatially resolved; therefore, its variable contributions to the slit spectra make the standard procedure of relative flux calibration impractical. We demonstrate that spatially-resolved data from the IFS can be effectively used to correct the slit-mask spectral light curves. While we obtained no reliable lag owing to the lack of strong variability pattern in the light curves, we constrain the broad line time lag to be less than 3 hr, consistent with the photometric lag of $\sim80$ min reported by Woo et al. (2019). By exploiting the high-quality spectra, we measure the second moment of the broad component of the H$α$ emission line to be $586\pm19$ km s$^{-1}$, superseding the lower value reported by Woo et al. (2019). Combining the revised line dispersion and the photometric time lag, we update the black hole mass as $(1.7\pm 0.3)\times10^4$ M$_{\odot}$.

astro-ph.GA↗

arXiv2021

GECKO Optical Follow-up Observation of Three Binary Black Hole Merger Events: GW190408_181802, GW190412, and GW190503_185404

We present optical follow-up observation results of three binary black hole merger (BBH) events, GW190408_181802, GW190412, and GW190503_185404, which were detected by the Advanced LIGO and Virgo gravitational wave (GW) detectors. Electromagnetic (EM) counterparts are generally not expected for BBH merger events. However, some theoretical models suggest that EM counterparts of BBH can possibly arise in special environments, prompting motivation to search for EM counterparts for such events. We observed high-credibility regions of the sky for the three BBH merger events with telescopes of the Gravitational-wave EM Counterpart Korean Observatory (GECKO), including the KMTNet. Our observation started as soon as 100 minutes after the GW event alerts and covered 29 - 63 deg$^2$ for each event with a depth of $\sim$ 22.5 mag in $R$-band within hours of observation. No plausible EM counterparts were found for these events, but from no detection in the GW190503_185404 event, for which we covered 69% credibility region, we place the BBH merger EM counterpart signal to be $M_{g}$ > -18.0 AB mag within about 1 day of the GW event. The comparison of our detection limits with light curves of several kilonova models suggests that a kilonova event could have been identified within hours from GW alert with GECKO observations if the compact merger happened at < 400 Mpc and the localization accuracy was of order of 50 deg$^2$. Our result gives a great promise for the GECKO facilities to find EM counterparts within a few hours from GW detection in future GW observation runs.

astro-ph.HE↗

arXiv2021

Cut-and-Paste Dataset Generation for Balancing Domain Gaps in Object Instance Detection

Training an object instance detector where only a few training object images are available is a challenging task. One solution is a cut-and-paste method that generates a training dataset by cutting object areas out of training images and pasting them onto other background images. A detector trained on a dataset generated with a cut-and-paste method suffers from the conventional domain shift problem, which stems from a discrepancy between the source domain (generated training dataset) and the target domain (real test dataset). Though state-of-the-art domain adaptation methods are able to reduce this gap, it is limited because they do not consider the difference of domain gaps of foreground and background. In this study, we present that the conventional domain gap can be divided into two sub-domain gaps for foreground and background. Then, we show that the original cut-and-paste approach suffers from a new domain gap problem, an unbalanced domain gaps, because it has two separate source domains for foreground and background, unlike the conventional domain shift problem. Then, we introduce an advanced cut-and-paste method to balance the unbalanced domain gaps by diversifying the foreground with GAN (generative adversarial network)-generated seed images and simplifying the background using image processing techniques. Experimental results show that our method is effective for balancing domain gaps and improving the accuracy of object instance detection in a cluttered indoor environment using only a few seed images. Furthermore, we show that balancing domain gaps can improve the detection accuracy of state-of-the-art domain adaptation methods.

cs.RO↗

arXiv2020

ExoClock Project: An open platform for monitoring the ephemerides of Ariel targets with contributions from the public

The Ariel mission will observe spectroscopically around 1000 exoplanets to further characterise their atmospheres. For the mission to be as efficient as possible, a good knowledge of the planets' ephemerides is needed before its launch in 2028. While ephemerides for some planets are being refined on a per-case basis, an organised effort to collectively verify or update them when necessary does not exist. In this study, we introduce the ExoClock project, an open, integrated and interactive platform with the purpose of producing a confirmed list of ephemerides for the planets that will be observed by Ariel. The project has been developed in a manner to make the best use of all available resources: observations reported in the literature, observations from space instruments and, mainly, observations from ground-based telescopes, including both professional and amateur observatories. To facilitate inexperienced observers and at the same time achieve homogeneity in the results, we created data collection and validation protocols, educational material and easy to use interfaces, open to everyone. ExoClock was launched in September 2019 and now counts over 140 participants from more than 15 countries around the world. In this release, we report the results of observations obtained until the 15h of April 2020 for 119 Ariel candidate targets. In total, 632 observations were used to either verify or update the ephemerides of 83 planets. Additionally, we developed the Exoplanet Characterisation Catalogue (ECC), a catalogue built in a consistent way to assist the ephemeris refinement process. So far, the collaborative open framework of the ExoClock project has proven to be highly efficient in coordinating scientific efforts involving diverse audiences. Therefore, we believe that it is a paradigm that can be applied in the future for other research purposes, too.

astro-ph.EP↗

arXiv2020

Original Research By Young Twinkle Students (ORBYTS): Ephemeris Refinement of Transiting Exoplanets

We report follow-up observations of transiting exoplanets that have either large uncertainties (>10 minutes) in their transit times or have not been observed for over three years. A fully robotic ground-based telescope network, observations from citizen astronomers and data from TESS have been used to study eight planets, refining their ephemeris and orbital data. Such follow-up observations are key for ensuring accurate transit times for upcoming ground and space-based telescopes which may seek to characterise the atmospheres of these planets. We find deviations from the expected transit time for all planets, with transits occurring outside the 1 sigma uncertainties for seven planets. Using the newly acquired observations, we subsequently refine their periods and reduce the current predicted ephemeris uncertainties to 0.28 - 4.01 minutes. A significant portion of this work has been completed by students at two high schools in London as part of the Original Research By Young Twinkle Students (ORBYTS) programme.

astro-ph.EP↗

arXiv2020

Variability and the size-luminosity relation of the intermediate mass AGN in NGC 4395

We present the variability study of the lowest-luminosity Seyfert 1 galaxy NGC 4395 based on the photometric monitoring campaigns in 2017 and 2018. Using 22 ground-based and space telescopes, we monitored NGC 4395 with a $\sim$5 minute cadence during a period of 10 days and obtained light curves in the UV, V, J, H, and K/Ks bands as well as the H$α$ narrow-band. The RMS variability is $\sim$0.13 mag on \emph{Swift}-UVM2 and V filter light curves, decreasing down to $\sim$0.01 mag on K filter. After correcting for continuum contribution to the H$α$ narrow-band, we measured the time lag of the H$α$ emission line with respect to the V-band continuum as ${55}^{+27}_{-31}$ to ${122}^{+33}_{-67}$ min. in 2017 and ${49}^{+15}_{-14}$ to ${83}^{+13}_{-14}$ min. in 2018, depending on the assumption on the continuum variability amplitude in the H$α$ narrow-band. We obtained no reliable measurements for the continuum-to-continuum lag between UV and V bands and among near-IR bands, due to the large flux uncertainty of UV observations and the limited time baseline. We determined the AGN monochromatic luminosity at 5100Å $λL_λ= \left(5.75\pm0.40\right)\times 10^{39}\,\mathrm{erg\,s^{-1}}$, after subtracting the contribution of the nuclear star cluster. While the optical luminosity of NGC 4395 is two orders of magnitude lower than that of other reverberation-mapped AGNs, NGC 4395 follows the size-luminosity relation, albeit with an offset of 0.48 dex ($\geq$2.5$σ$) from the previous best-fit relation of Bentz et al. (2013).

astro-ph.GA↗

arXiv2020

C-3PO: Cyclic-Three-Phase Optimization for Human-Robot Motion Retargeting based on Reinforcement Learning

Motion retargeting between heterogeneous polymorphs with different sizes and kinematic configurations requires a comprehensive knowledge of (inverse) kinematics. Moreover, it is non-trivial to provide a kinematic independent general solution. In this study, we developed a cyclic three-phase optimization method based on deep reinforcement learning for human-robot motion retargeting. The motion retargeting learning is performed using refined data in a latent space by the cyclic and filtering paths of our method. In addition, the human-in-the-loop based three-phase approach provides a framework for the improvement of the motion retargeting policy by both quantitative and qualitative manners. Using the proposed C-3PO method, we were successfully able to learn the motion retargeting skill between the human skeleton and motion of the multiple robots such as NAO, Pepper, Baxter and C-3PO.

cs.RO↗