13 citations · 17 across the 6 of their papers we have counts for
6 papers
Mesh Represented Recycle Learning for 3D Hand Pose and Mesh Estimation
Bosang Kim, Jonghyun Kim, Hyotae Lee +7
In general, hand pose estimation aims to improve the robustness of model performance in the real-world scenes. However, it is difficult to enhance the robustness since existing dat…
Hybrid model for Single-Stage Multi-Person Pose Estimation
Jonghyun Kim, Bosang Kim, Hyotae Lee +5
In general, human pose estimation methods are categorized into two approaches according to their architectures: regression (i.e., heatmap-free) and heatmap-based methods. The forme…
Leveraging Spatio-Temporal Dependency for Skeleton-Based Action Recognition
Jungho Lee, Minhyeok Lee, Suhwan Cho +3
Skeleton-based action recognition has attracted considerable attention due to its compact representation of the human body's skeletal sructure. Many recent methods have achieved re…
Hierarchically Decomposed Graph Convolutional Networks for Skeleton-Based Action Recognition
Jungho Lee, Minhyeok Lee, Dogyoon Lee +1
Graph convolutional networks (GCNs) are the most commonly used methods for skeleton-based action recognition and have achieved remarkable performance. Generating adjacency matrices…
M2FN: Multi-step Modality Fusion for Advertisement Image Assessment
Kyung-Wha Park, Jung-Woo Ha, JungHoon Lee +3
Assessing advertisements, specifically on the basis of user preferences and ad quality, is crucial to the marketing industry. Although recent studies have attempted to use deep neu…
Which Ads to Show? Advertisement Image Assessment with Auxiliary Information via Multi-step Modality Fusion
Kyung-Wha Park, JungHoon Lee, Sunyoung Kwon +3
Assessing aesthetic preference is a fundamental task related to human cognition. It can also contribute to various practical applications such as image creation for online advertis…