activity
20162023
most citedLexicon-Free Fingerspelling Recognition from Video: Data, Models, and Signer Adaptation

3 citations · 5 across the 6 of their papers we have counts for

collaborators

6 papers

cs.MM2023

Sound of Story: Multi-modal Storytelling with Audio

Jaeyeon Bae, Seokhoon Jeong, Seokun Kang +4

Storytelling is multi-modal in the real world. When one tells a story, one may use all of the visualizations and sounds along with the story itself. However, prior studies on story…

cs.CL2023

Effective Slogan Generation with Noise Perturbation

Jongeun Kim, MinChung Kim, Taehwan Kim

Slogans play a crucial role in building the brand's identity of the firm. A slogan is expected to reflect firm's vision and brand's value propositions in memorable and likeable way…

cs.CV2023

Generating Realistic Images from In-the-wild Sounds

Taegyeong Lee, Jeonghun Kang, Hyeonyu Kim +1

Representing wild sounds as images is an important but challenging task due to the lack of paired datasets between sound and images and the significant differences in the character…

cs.CV2022

Technical Report for CVPR 2022 LOVEU AQTC Challenge

Hyeonyu Kim, Jongeun Kim, Jeonghun Kang +3

This technical report presents the 2nd winning model for AQTC, a task newly introduced in CVPR 2022 LOng-form VidEo Understanding (LOVEU) challenges. This challenge faces difficult…

cs.CL20163 cited

Lexicon-Free Fingerspelling Recognition from Video: Data, Models, and Signer Adaptation

Taehwan Kim, Jonathan Keane, Weiran Wang +5

We study the problem of recognizing video sequences of fingerspelled letters in American Sign Language (ASL). Fingerspelling comprises a significant but relatively understudied par…

cs.CL20162 cited

American Sign Language fingerspelling recognition from video: Methods for unrestricted recognition and signer-independence

Taehwan Kim

In this thesis, we study the problem of recognizing video sequences of fingerspelled letters in American Sign Language (ASL). Fingerspelling comprises a significant but relatively…