← Search

Minyoung Jung

5 accepted papers

2023

Liveness Score-Based Regression Neural Networks for Face Anti-Spoofing

ICASSP 2023accepted

Previous anti-spoofing methods have used either pseudo maps or user-defined labels, and the performance of each approach depends on the accuracy of the third party networks generating pseudo maps and the way in which the users define the labels. In this paper, we propose a liveness score-based regre…

Cited by 0SourceScholar
2023

ProtoFL: Unsupervised Federated Learning via Prototypical Distillation

ICCV 2023poster

Federated learning (FL) is a promising approach for enhancing data privacy preservation, particularly for authentication systems. However, limited round communications, scarce representation, and scalability pose significant challenges to its deployment, hindering its full potential. In this paper,…

Cited by 13PDFScholar
2021

A Model of Cross-Lingual Knowledge-Grounded Response Generation for Open-Domain Dialogue Systems

EMNLP 2021finding

Research on open-domain dialogue systems that allow free topics is challenging in the field of natural language processing (NLP). The performance of the dialogue system has been improved recently by the method utilizing dialogue-related knowledge; however, non-English dialogue systems suffer from re…

2021

BPM_MT: Enhanced Backchannel Prediction Model using Multi-Task Learning

EMNLP 2021main

Backchannel (BC), a short reaction signal of a listener to a speaker’s utterances, helps to improve the quality of the conversation. Several studies have been conducted to predict BC in conversation; however, the utilization of advanced natural language processing techniques using lexical informatio…

2021

MIND dataset for diet planning and dietary healthcare with machine learning: Dataset creation using combinatorial optimization and controllable generation with domain experts

NeurIPS 2021poster

Diet planning, a basic and regular human activity, is important to all individuals. Children, adults, the healthy, and the infirm all profit from diet planning. Many recent attempts have been made to develop machine learning (ML) applications related to diet planning. However, given the complexity a…

Cited by 6SourceScholar