activity
20222025
most citedCross-Domain Style Mixing for Face Cartoonization

5 citations · 7 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2025

VisAgent: Narrative-Preserving Story Visualization Framework

Seungkwon Kim, GyuTae Park, Sangyeon Kim +1

Story visualization is the transformation of narrative elements into image sequences. While existing research has primarily focused on visual contextual coherence, the deeper narra…

cs.CV2024

A Framework for Portrait Stylization with Skin-Tone Awareness and Nudity Identification

Seungkwon Kim, Sangyeon Kim, Seung-Hun Nam

Portrait stylization is a challenging task involving the transformation of an input portrait image into a specific style while preserving its inherent characteristics. The recent i…

cs.CV2022★ 1 cited

Interactive Cartoonization with Controllable Perceptual Factors

Namhyuk Ahn, Patrick Kwon, Jihye Back +2

Cartoonization is a task that renders natural photos into cartoon styles. Previous deep cartoonization methods only have focused on end-to-end translation, which may hinder editabi…

cs.CV2022★ 1 cited

WebtoonMe: A Data-Centric Approach for Full-Body Portrait Stylization

Jihye Back, Seungkwon Kim, Namhyuk Ahn

Full-body portrait stylization, which aims to translate portrait photography into a cartoon style, has drawn attention recently. However, most methods have focused only on converti…

cs.CV2022★ 5 cited

Cross-Domain Style Mixing for Face Cartoonization

Seungkwon Kim, Chaeheon Gwak, Dohyun Kim +4

Cartoon domain has recently gained increasing popularity. Previous studies have attempted quality portrait stylization into the cartoon domain; however, this poses a great challeng…