Avoiding overfitting: A survey on regularization methods for convolutional neural networks
CFGD Santos, JP Papa - ACM Computing Surveys (CSUR), 2022 - dl.acm.org
Several image processing tasks, such as image classification and object detection, have
been significantly improved using Convolutional Neural Networks (CNN). Like ResNet and …
been significantly improved using Convolutional Neural Networks (CNN). Like ResNet and …
Occluded person re-identification with deep learning: a survey and perspectives
Person re-identification (Re-ID) technology plays an increasingly crucial role in intelligent
surveillance systems. Widespread occlusion significantly impacts the performance of person …
surveillance systems. Widespread occlusion significantly impacts the performance of person …
Part-based pseudo label refinement for unsupervised person re-identification
Unsupervised person re-identification (re-ID) aims at learning discriminative representations
for person retrieval from unlabeled data. Recent techniques accomplish this task by using …
for person retrieval from unlabeled data. Recent techniques accomplish this task by using …
Diverse part discovery: Occluded person re-identification with part-aware transformer
Occluded person re-identification (Re-ID) is a challenging task as persons are frequently
occluded by various obstacles or other persons, especially in the crowd scenario. To …
occluded by various obstacles or other persons, especially in the crowd scenario. To …
Channel augmented joint learning for visible-infrared recognition
This paper introduces a powerful channel augmented joint learning strategy for the visible-
infrared recognition problem. For data augmentation, most existing methods directly adopt …
infrared recognition problem. For data augmentation, most existing methods directly adopt …
Learning by aligning: Visible-infrared person re-identification using cross-modal correspondences
We address the problem of visible-infrared person re-identification (VI-reID), that is,
retrieving a set of person images, captured by visible or infrared cameras, in a cross-modal …
retrieving a set of person images, captured by visible or infrared cameras, in a cross-modal …
Towards real-time multi-object tracking
Modern multiple object tracking (MOT) systems usually follow the tracking-by-detection
paradigm. It has 1) a detection model for target localization and 2) an appearance …
paradigm. It has 1) a detection model for target localization and 2) an appearance …
Unsupervised person re-identification via multi-label classification
The challenge of unsupervised person re-identification (ReID) lies in learning discriminative
features without true labels. This paper formulates unsupervised person ReID as a multi …
features without true labels. This paper formulates unsupervised person ReID as a multi …
High-order information matters: Learning relation and topology for occluded person re-identification
Occluded person re-identification (ReID) aims to match occluded person images to holistic
ones across dis-joint cameras. In this paper, we propose a novel framework by learning high …
ones across dis-joint cameras. In this paper, we propose a novel framework by learning high …