Search Results for author:
Found 4 papers, 1 papers with code
Robust Pedestrian Detection via Constructing Versatile Pedestrian Knowledge Bank
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.
Integrating Language-Derived Appearance Elements with Visual Cues in Pedestrian Detection
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.
Meta Input: How to Leverage Off-the-Shelf Deep Neural Networks
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.
Robust Small-Scale Pedestrian Detection With Cued Recall via Memory Learning
The purpose of the proposed large-scale embedding learning is to memorize and recall the large-scale pedestrian appearance via the LPR Memory.
