1 citations · 1 across the 3 of their papers we have counts for
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Difficulty-aware Balancing Margin Loss for Long-tailed Recognition
Minseok Son, Inyong Koo, Jinyoung Park +1
When trained with severely imbalanced data, deep neural networks often struggle to accurately recognize classes with only a few samples. Previous studies in long-tailed recognition…
DiffRef3D: A Diffusion-based Proposal Refinement Framework for 3D Object Detection
Se-Ho Kim, Inyong Koo, Inyoung Lee +2
Denoising diffusion models show remarkable performances in generative tasks, and their potential applications in perception tasks are gaining interest. In this paper, we introduce…
PG-RCNN: Semantic Surface Point Generation for 3D Object Detection
Inyong Koo, Inyoung Lee, Se-Ho Kim +3
One of the main challenges in LiDAR-based 3D object detection is that the sensors often fail to capture the complete spatial information about the objects due to long distance and…
Improving Few-shot Learning with Weakly-supervised Object Localization
Inyong Koo, Minki Jeong, Changick Kim
Few-shot learning often involves metric learning-based classifiers, which predict the image label by comparing the distance between the extracted feature vector and class represent…