Nov 29, 2019 · We propose a novel pedestrian detection method, which handles the scale variation problem by processing proposals of different scales using ...

To address this problem, this paper presents a novel pedestrian detector to better classify and regress proposals of different scales given by a region proposal ...

Serious scale variation is a key challenge in pedestrian detection. Most works typically employ a feature pyramid network to detect objects at diverse scales.

This paper explores the research status of pedestrian detection in the past four years (2019–2022), focuses on analyzing the occlusion and scale problems of ...

In this study, we proposed a new pedestrian detection algorithm based on multi-scale feature extraction and attention feature fusion, which is called MSAF-Net.

Jul 24, 2015 · Hence, the HOG feature is actually the most efficient and fundamental feature for pedestrian detection. However, the HOG feature cannot ...

First, we propose a scale-discriminative classifier layer that is sensitive to pedes- trian scale, to improve performance in scale-variant pedes- trian ...

Generic Hard Pattern Handling The central key to han- dling hard patterns of scale variation and occlusion is accu- rate localization. ALFNet (Liu et al. 2018), ...

Aug 18, 2022 · In order to handle scale-variance and improve small-scale instances detection performance, we expect to see feature maps with different ...

Jun 25, 2016 · The model introduces multiple built-in sub- networks which detect pedestrians with scales from disjoint ranges. Outputs from all the sub- ...