no code implementations • 30 Apr 2024 • Sungjune Park, Hyunjun Kim, Yong Man Ro
Therefore, in this paper, we propose a novel approach to construct versatile pedestrian knowledge bank containing representative pedestrian knowledge which can be applicable to various detection frameworks and adopted in diverse scenes.
1 code implementation • 2 Nov 2023 • Sungjune Park, Hyunjun Kim, Yong Man Ro
The obtained knowledge elements are adaptable to various detection frameworks, so that we can provide plentiful appearance information by integrating the language-derived appearance elements with visual cues within a detector.
no code implementations • 21 Oct 2022 • Minsu Kim, Youngjoon Yu, Sungjune Park, Yong Man Ro
The proposed meta input can be optimized with a small number of testing data only by considering the relation between testing input data and its output prediction.
no code implementations • ICCV 2021 • Jung Uk Kim, Sungjune Park, Yong Man Ro
The purpose of the proposed large-scale embedding learning is to memorize and recall the large-scale pedestrian appearance via the LPR Memory.