A comprehensive survey on human pose estimation approaches
The human pose estimation is a significant issue that has been taken into consideration in
the computer vision network for recent decades. It is a vital advance toward understanding …
the computer vision network for recent decades. It is a vital advance toward understanding …
Detection in crowded scenes: One proposal, multiple predictions
We propose a simple yet effective proposal-based object detector, aiming at detecting highly-
overlapped instances in crowded scenes. The key of our approach is to let each proposal …
overlapped instances in crowded scenes. The key of our approach is to let each proposal …
Occlusion handling and multi-scale pedestrian detection based on deep learning: A review
F Li, X Li, Q Liu, Z Li - IEEE Access, 2022 - ieeexplore.ieee.org
Pedestrian detection is an important branch of computer vision, and has important
applications in the fields of autonomous driving, artificial intelligence and video surveillance …
applications in the fields of autonomous driving, artificial intelligence and video surveillance …
Progressive end-to-end object detection in crowded scenes
In this paper, we propose a new query-based detection framework for crowd detection.
Previous query-based detectors suffer from two drawbacks: first, multiple predictions will be …
Previous query-based detectors suffer from two drawbacks: first, multiple predictions will be …
From handcrafted to deep features for pedestrian detection: A survey
Pedestrian detection is an important but challenging problem in computer vision, especially
in human-centric tasks. Over the past decade, significant improvement has been witnessed …
in human-centric tasks. Over the past decade, significant improvement has been witnessed …
Online multi-object tracking with unsupervised re-identification learning and occlusion estimation
Occlusion between different objects is a typical challenge in Multi-Object Tracking (MOT),
which often leads to inferior tracking results due to the missing detected objects. The …
which often leads to inferior tracking results due to the missing detected objects. The …
Vlpd: Context-aware pedestrian detection via vision-language semantic self-supervision
Detecting pedestrians accurately in urban scenes is significant for realistic applications like
autonomous driving or video surveillance. However, confusing human-like objects often …
autonomous driving or video surveillance. However, confusing human-like objects often …
TJU-DHD: A diverse high-resolution dataset for object detection
Vehicles, pedestrians, and riders are the most important and interesting objects for the
perception modules of self-driving vehicles and video surveillance. However, the state-of-the …
perception modules of self-driving vehicles and video surveillance. However, the state-of-the …
Autopedestrian: An automatic data augmentation and loss function search scheme for pedestrian detection
Pedestrian detection is a challenging and hot research topic in the field of computer vision,
especially for the crowded scenes where occlusion happens frequently. In this paper, we …
especially for the crowded scenes where occlusion happens frequently. In this paper, we …
Detr for crowd pedestrian detection
Pedestrian detection in crowd scenes poses a challenging problem due to the heuristic
defined mapping from anchors to pedestrians and the conflict between NMS and highly …
defined mapping from anchors to pedestrians and the conflict between NMS and highly …