Pedestrian detection in the wild remains a challenging problem especially for scenes
containing serious occlusion. In this paper, we propose a novel feature learning method in …

In this paper, a self-learning approach is proposed towards solving scene-specific
pedestrian detection problem without any human'annotation involved. The self-learning …

Recently, pedestrian detection on thermal infrared images has shown the robust pedestrian
detection performance. In this paper, we propose a novel thermal infrared pedestrian …

This paper tackles the problem of data selection for training set generation in the context of
near real-time pedestrian detection through the introduction of a training methodology …

Pedestrian detection in the wild remains a challenging problem especially when the scene
contains significant occlusion and/or low resolution of the pedestrians to be detected …

This paper presents a new deep learning architecture for robust object representation,
aiming at efficiently combining the proposed synchronized multi-stage feature (SMF) and a …

Pedestrian detection attracts lots of attentions in the field of computer vision in recent years.
It is difficult to handle data imbalance between positive and negative examples and easy-to …

This paper introduces a new channel descriptor for pedestrian detection. This type of
descriptor usually selects a set of one-valued filters within the enormous set of all possible …

Conventional pedestrian detection methods construct models based on hand-crafted
features or deep learning. They are powerful but limited due to finite capabilities of single …

The performance of offline learned pedestrian detectors significantly drops when they are
applied to video scenes of various camera views, occlusions, and background structures …