MultiMedia Modeling
26th International Conference, MMM 2020, Daejeon, South Korea, January 5–8, 2020, Proceedings, Part I
Chapter and Conference Paper
This paper presents the details of the proposed video retrieval tool, named Interactive VIdeo Search Tool (IVIST) for the Video Browser Showdown (VBS) 2022. In order to retrieve desired videos from a multimedi...
Chapter and Conference Paper
Lip reading aims to predict speech based on lip movements alone. As it focuses on visual information to model the speech, its performance is inherently sensitive to personal lip appearances and movements. This...
Chapter and Conference Paper
Retrieving desired videos using natural language queries has attracted increasing attention in research and industry fields as a huge number of videos appear on the internet. Some existing methods attempted to...
Chapter and Conference Paper
The goal of this work is to reconstruct speech from a silent talking face video. Recent studies have shown impressive performance on synthesizing speech from silent talking face videos. However, they have not ...
Chapter and Conference Paper
With the development of deep neural networks, multispectral pedestrian detection has been received a great attention by exploiting complementary properties of multiple modalities (e.g., color-visible and thermal ...
Chapter and Conference Paper
This paper presents a new version of the Interactive VIdeo Search Tool (IVIST), a video retrieval tool, for the participation of the Video Browser Showdown (VBS) 2021. In the previous IVIST (VBS 2020), there w...
Chapter and Conference Paper
The original version of this book was revised. Due to a technical error, the first volume editor did not appear in the volumes of the MMM 2020 proceedings. This was corrected and the first volume editor was ad...
Book and Conference Proceedings
26th International Conference, MMM 2020, Daejeon, South Korea, January 5–8, 2020, Proceedings, Part I
Book and Conference Proceedings
26th International Conference, MMM 2020, Daejeon, South Korea, January 5–8, 2020, Proceedings, Part II
Chapter and Conference Paper
This paper presents a new video retrieval tool, Interactive VIdeo Search Tool (IVIST), which participates in the 2020 Video Browser Showdown (VBS). As a video retrieval tool, IVIST is equipped with proper and...
Chapter and Conference Paper
Human facial expression plays the key role in the understanding of the social behavior. Many deep learning approaches present facial emotion recognition and automatic image captioning considering human sentime...
Chapter and Conference Paper
This paper introduces a video retrieval tool for the 2020 Video Browser Showdown (VBS). The tool enhances the user’s video browsing experience by ensuring full use of video analysis database constructed prior ...
Chapter and Conference Paper
The original version of this book was revised. Due to a technical error, the first volume editor did not appear in the volumes of the MMM 2020 proceedings. A funding number was missing in the acknowledgement s...
Chapter and Conference Paper
Recently, cybersickness assessment for VR content is required to deal with viewing safety issues. Assessing physical symptoms of individual viewers is challenging but important to provide detailed and personal...
Article
Although there is an abundance of current research on facial recognition, it still faces significant challenges that are related to variations in factors such as aging, poses, occlusions, resolution, and appea...
Chapter and Conference Paper
This paper deals with a method for generating realistic labeled masses. Recently, there have been many attempts to apply deep learning to various bio-image computing fields including computer-aided detection a...
Chapter and Conference Paper
In this paper, we propose photo-realistic facial emotion synthesis by using a novel multi-level critic network with multi-level generative model. We devise a new facial emotion generator containing the propose...
Chapter and Conference Paper
The ambiguity of the decision-making process has been pointed out as the main obstacle to practically applying the deep learning-based method in spite of its outstanding performance. Interpretability can guara...
Chapter and Conference Paper
Generating realistic breast masses is a highly important task because the large-size database of annotated breast masses is scarcely available. In this study, a novel realistic breast mass generation framework...
Chapter and Conference Paper
Compact neural networks with limited memory and computation are demanding in recently popularized mobile applications. The reduction of network parameters is an important priority. In this paper, we address a ...