21 citations · 54 across the 8 of their papers we have counts for
8 papers
Understanding and Tackling Over-Dilution in Graph Neural Networks
Junhyun Lee, Veronika Thost, Bumsoo Kim +2
Message Passing Neural Networks (MPNNs) hold a key position in machine learning on graphs, but they struggle with unintended behaviors, such as over-smoothing and over-squashing, d…
Generative Modeling of Class Probability for Multi-Modal Representation Learning
Jungkyoo Shin, Bumsoo Kim, Eunwoo Kim
Multi-modal understanding plays a crucial role in artificial intelligence by enabling models to jointly interpret inputs from different modalities. However, conventional approaches…
Is 'Right' Right? Enhancing Object Orientation Understanding in Multimodal Large Language Models through Egocentric Instruction Tuning
Ji Hyeok Jung, Eun Tae Kim, Seoyeon Kim +3
Multimodal large language models (MLLMs) act as essential interfaces, connecting humans with AI technologies in multimodal applications. However, current MLLMs face challenges in a…
UnionDet: Union-Level Detector Towards Real-Time Human-Object Interaction Detection
Bumsoo Kim, Taeho Choi, Jaewoo Kang +1
Recent advances in deep neural networks have achieved significant progress in detecting individual objects from an image. However, object detection is not sufficient to fully under…
Co-attention Graph Pooling for Efficient Pairwise Graph Interaction Learning
Junhyun Lee, Bumsoo Kim, Minji Jeon +1
Graph Neural Networks (GNNs) have proven to be effective in processing and learning from graph-structured data. However, previous works mainly focused on understanding single graph…
UniCLIP: Unified Framework for Contrastive Language-Image Pre-training
Janghyeon Lee, Jongsuk Kim, Hyounguk Shon +4
Pre-training vision-language models with contrastive objectives has shown promising results that are both scalable to large uncurated datasets and transferable to many downstream a…
MSTR: Multi-Scale Transformer for End-to-End Human-Object Interaction Detection
Bumsoo Kim, Jonghwan Mun, Kyoung-Woon On +3
Human-Object Interaction (HOI) detection is the task of identifying a set of <human, object, interaction> triplets from an image. Recent work proposed transformer encoder-decoder a…
HOTR: End-to-End Human-Object Interaction Detection with Transformers
Bumsoo Kim, Junhyun Lee, Jaewoo Kang +2
Human-Object Interaction (HOI) detection is a task of identifying "a set of interactions" in an image, which involves the i) localization of the subject (i.e., humans) and target (…