1 citations · 2 across the 5 of their papers we have counts for
5 papers
SMILE-Next: Teaching Large Language Models to Detect, Classify, and Reason about Laughter
Lee Jung-Mok, Kim Sung-Bin, Joohyun Chang +2
Laughter is a complex social signal that conveys communicative intent beyond amusement. While prior work has focused on isolated laughter analysis tasks, a comprehensive understand…
VLM's Eye Examination: Instruct and Inspect Visual Competency of Vision Language Models
Nam Hyeon-Woo, Moon Ye-Bin, Wonseok Choi +2
Vision language models (VLMs) have shown promising reasoning capabilities across various benchmarks; however, our understanding of their visual perception remains limited. In this…
SMILE: Multimodal Dataset for Understanding Laughter in Video with Language Models
Lee Hyun, Kim Sung-Bin, Seungju Han +2
Despite the recent advances of the artificial intelligence, building social intelligence remains a challenge. Among social signals, laughter is one of the distinctive expressions t…
LaughTalk: Expressive 3D Talking Head Generation with Laughter
Kim Sung-Bin, Lee Hyun, Da Hye Hong +3
Laughter is a unique expression, essential to affirmative social interactions of humans. Although current 3D talking head generation methods produce convincing verbal articulations…
A Large-Scale 3D Face Mesh Video Dataset via Neural Re-parameterized Optimization
Kim Youwang, Lee Hyun, Kim Sung-Bin +3
We propose NeuFace, a 3D face mesh pseudo annotation method on videos via neural re-parameterized optimization. Despite the huge progress in 3D face reconstruction methods, generat…