arXiv subjects

Yongjun Wu

Publications and source records attributed to Yongjun Wu.

25 records · Page 2Linked to original sources

arXiv2021

ChipQA: No-Reference Video Quality Prediction via Space-Time Chips

We propose a new model for no-reference video quality assessment (VQA). Our approach uses a new idea of highly-localized space-time (ST) slices called Space-Time Chips (ST Chips). ST Chips are localized cuts of video data along directions that \textit{implicitly} capture motion. We use perceptually-motivated bandpass and normalization models to first process the video data, and then select oriented ST Chips based on how closely they fit parametric models of natural video statistics. We show that the parameters that describe these statistics can be used to reliably predict the quality of videos, without the need for a reference video. The proposed method implicitly models ST video naturalness, and deviations from naturalness. We train and test our model on several large VQA databases, and show that our model achieves state-of-the-art performance at reduced cost, without requiring motion computation.

eess.IV↗

arXiv2021

Local Manipulation of Polar Skyrmions and Topological Phase Transitions

Topological phases such as polar skyrmions have been a fertile playground for ferroelectric oxide superlattices, with exotic physical phenomena such as negative capacitance. Herein, using phase-field simulations, we demonstrate the local control of the skyrmion phase with electric potential applied through a top electrode. Under a relatively small electric potential, the skyrmions underneath the electrode can be erased and recovered reversibly. A topologically protected transition from the symmetric to asymmetric skyrmion bubbles is observed at the edge of the electrode. While a topological transition to a labyrinthine domain requires a high applied potential, it can switch back to the skyrmion state with a relatively small electric potential. The topological transition from +1 to 0 occurs before the full destruction of the bubble state. It is shown that the shrinking and bursting of the skyrmions leads to a large reduction in the dielectric permittivity, the magnitude of which depends on the size of the electrode.

cond-mat.mtrl-sci↗

arXiv2021

Assessment of Subjective and Objective Quality of Live Streaming Sports Videos

Video live streaming is gaining prevalence among video streaming services, especially for the delivery of popular sporting events. Many objective Video Quality Assessment (VQA) models have been developed to predict the perceptual quality of videos. Appropriate databases that exemplify the distortions encountered in live streaming videos are important to designing and learning objective VQA models. Towards making progress in this direction, we built a video quality database specifically designed for live streaming VQA research. The new video database is called the Laboratory for Image and Video Engineering (LIVE) Live stream Database. The LIVE Livestream Database includes 315 videos of 45 contents impaired by 6 types of distortions. We also performed a subjective quality study using the new database, whereby more than 12,000 human opinions were gathered from 40 subjects. We demonstrate the usefulness of the new resource by performing a holistic evaluation of the performance of current state-of-the-art (SOTA) VQA models. The LIVE Livestream database is being made publicly available for these purposes at https://live.ece.utexas.edu/research/LIVE_APV_Study/apv_index.html.

eess.IV↗

arXiv2021

Detection of Audio-Video Synchronization Errors Via Event Detection

We present a new method and a large-scale database to detect audio-video synchronization(A/V sync) errors in tennis videos. A deep network is trained to detect the visual signature of the tennis ball being hit by the racquet in the video stream. Another deep network is trained to detect the auditory signature of the same event in the audio stream. During evaluation, the audio stream is searched by the audio network for the audio event of the ball being hit. If the event is found in audio, the neighboring interval in video is searched for the corresponding visual signature. If the event is not found in the video stream but is found in the audio stream, A/V sync error is flagged. We developed a large-scaled database of 504,300 frames from 6 hours of videos of tennis events, simulated A/V sync errors, and found our method achieves high accuracy on the task.

cs.MM↗

arXiv2021

Machine Learning Enabled Prediction of Cathode Materials for Zn ion Batteries

Rechargeable Zn batteries with aqueous electrolytes have been considered as promising alternative energy storage technology, with various advantages such as low cost, high volumetric capacity, environmentally friendly, and high safety. However, a lack of reliable cathode materials has largely pledged their applications. Herein, we developed a machine learning (ML) based approach to predict cathodes with high capacity (>150 mAh/g) and high voltage (>0.5V). We screened over ~130,000 inorganic materials from the Materials Project database and applied the crystal graph convolutional neural network (CGCNN) based ML approach with data from the AFLOW database. The combination of these two could not only screen cathode materials that match well with the experimental data but also predict new promising candidates for further experimental validations. We hope this study could spur further interests in ML-based advanced theoretical tools for battery materials discovery.

cond-mat.mtrl-sci↗

arXiv2020

No-Reference Video Quality Assessment Using Space-Time Chips

We propose a new prototype model for no-reference video quality assessment (VQA) based on the natural statistics of space-time chips of videos. Space-time chips (ST-chips) are a new, quality-aware feature space which we define as space-time localized cuts of video data in directions that are determined by the local motion flow. We use parametrized distribution fits to the bandpass histograms of space-time chips to characterize quality, and show that the parameters from these models are affected by distortion and can hence be used to objectively predict the quality of videos. Our prototype method, which we call ChipQA-0, is agnostic to the types of distortion affecting the video, and is based on identifying and quantifying deviations from the expected statistics of natural, undistorted ST-chips in order to predict video quality. We train and test our resulting model on several large VQA databases and show that our model achieves high correlation against human judgments of video quality and is competitive with state-of-the-art models.

eess.IV↗

arXiv2011

A top-down approach for desynchronization in an ensemble of coupled oscillators

A universal approach is proposed for suppression of collective synchrony in a large population of interacting rhythmic units. We demonstrate that provided that the internal coupling is weak, stabilization of overall oscillations with vanishing stimulation leads to desynchronization in a large ensemble of coupled oscillators, without altering significantly the essential nature of each constituent oscillator. We expect our findings to be a starting point for the issue of destroying undesired synchronization, e. g. desynchronization techniques for deep brain stimulation for neurological diseases characterized by pathological neural synchronization.

nlin.AO↗