no code implementations • 25 Oct 2022 • Youngin Cho, Junsoo Lee, Soyoung Yang, Juntae Kim, Yeojeong Park, Haneol Lee, Mohammad Azam Khan, Daesik Kim, Jaegul Choo
Existing deep interactive colorization models have focused on ways to utilize various types of interactions, such as point-wise color hints, scribbles, or natural-language texts, as methods to reflect a user's intent at runtime.
1 code implementation • 25 May 2022 • Seungkwon Kim, Chaeheon Gwak, Dohyun Kim, Kwangho Lee, Jihye Back, Namhyuk Ahn, Daesik Kim
Cartoon domain has recently gained increasing popularity.
no code implementations • 25 Feb 2021 • Inseop Chung, Daesik Kim, Nojun Kwak
We propose a novel method that tackles the problem of unsupervised domain adaptation for semantic segmentation by maximizing the cosine similarity between the source and the target domain at the feature level.
no code implementations • 14 Aug 2020 • Seung-Hun Nam, In-Jae Yu, Seung-Min Mun, Daesik Kim, Wonhyuk Ahn
Multi-bit watermarking (MW) has been developed to improve robustness against signal processing operations and geometric distortions.
no code implementations • 19 Nov 2019 • Daesik Kim, Gyujeong Lee, Jisoo Jeong, Nojun Kwak
In the source domain, we fully train an object detector and the RRPN with full supervision of HOI.
no code implementations • ACL 2019 • Daesik Kim, Seonhoon Kim, Nojun Kwak
Moreover, ablation studies validate that both methods of incorporating f-GCN for extracting knowledge from multi-modal contexts and our newly proposed self-supervised learning process are effective for TQA problems.
no code implementations • 9 Jul 2018 • Jeesoo Kim, Jangho Kim, Jaeyoung Yoo, Daesik Kim, Nojun Kwak
Using a subnetwork based on a precedent work of image completion, our model makes the shape of an object.
no code implementations • CVPR 2018 • Daesik Kim, Youngjoon Yoo, Jeesoo Kim, Sangkuk Lee, Nojun Kwak
In this work, we introduce a new algorithm for analyzing a diagram, which contains visual and textual information in an abstract and integrated way.
no code implementations • 2 Jul 2017 • Sangkuk Lee, Daesik Kim, Myunggi Lee, Jihye Hwang, Nojun Kwak
Through quantitative and qualitative evaluation, we show that our method is effective for retrieval of video segments using natural language queries.