23 citations · 92 across the 20 of their papers we have counts for
5 papers · 1 filter
Deep Hash Distillation for Image Retrieval
Young Kyun Jang, Geonmo Gu, Byungsoo Ko +2
In hash-based image retrieval systems, degraded or transformed inputs usually generate different codes from the original, deteriorating the retrieval accuracy. To mitigate this iss…
Towards Light-weight and Real-time Line Segment Detection
Geonmo Gu, Byungsoo Ko, SeoungHyun Go +3
Previous deep learning-based line segment detection (LSD) suffers from the immense model size and high computational cost for line prediction. This constrains them from real-time i…
RTIC: Residual Learning for Text and Image Composition using Graph Convolutional Network
Minchul Shin, Yoonjae Cho, Byungsoo Ko +1
In this paper, we study the compositional learning of images and texts for image retrieval. The query is given in the form of an image and text that describes the desired modificat…
Proxy Synthesis: Learning with Synthetic Classes for Deep Metric Learning
Geonmo Gu, Byungsoo Ko, Han-Gyu Kim
One of the main purposes of deep metric learning is to construct an embedding space that has well-generalized embeddings on both seen (training) classes and unseen (test) classes.…
Learning with Memory-based Virtual Classes for Deep Metric Learning
Byungsoo Ko, Geonmo Gu, Han-Gyu Kim
The core of deep metric learning (DML) involves learning visual similarities in high-dimensional embedding space. One of the main challenges is to generalize from seen classes of t…