45 citations · 55 across the 6 of their papers we have counts for
6 papers
Context-Preserving Two-Stage Video Domain Translation for Portrait Stylization
Doyeon Kim, Eunji Ko, Hyunsu Kim +5
Portrait stylization, which translates a real human face image into an artistically stylized image, has attracted considerable interest and many prior works have shown impressive q…
StyleLipSync: Style-based Personalized Lip-sync Video Generation
Taekyung Ki, Dongchan Min
In this paper, we present StyleLipSync, a style-based personalized lip-sync video generative model that can generate identity-agnostic lip-synchronizing video from arbitrary audio.…
Grad-StyleSpeech: Any-speaker Adaptive Text-to-Speech Synthesis with Diffusion Models
Minki Kang, Dongchan Min, Sung Ju Hwang
There has been a significant progress in Text-To-Speech (TTS) synthesis technology in recent years, thanks to the advancement in neural generative modeling. However, existing metho…
StyleTalker: One-shot Style-based Audio-driven Talking Head Video Generation
Dongchan Min, Minyoung Song, Eunji Ko +1
We propose StyleTalker, a novel audio-driven talking head generation model that can synthesize a video of a talking person from a single reference image with accurately audio-synce…
Distortion-Aware Network Pruning and Feature Reuse for Real-time Video Segmentation
Hyunsu Rhee, Dongchan Min, Sunil Hwang +2
Real-time video segmentation is a crucial task for many real-world applications such as autonomous driving and robot control. Since state-of-the-art semantic segmentation models ar…
Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation
Dongchan Min, Dong Bok Lee, Eunho Yang +1
With rapid progress in neural text-to-speech (TTS) models, personalized speech generation is now in high demand for many applications. For practical applicability, a TTS model shou…