[HTML][HTML] Survey and performance analysis of deep learning based object detection in challenging environments

M Ahmed, KA Hashmi, A Pagani, M Liwicki, D Stricker… - Sensors, 2021 - mdpi.com
Recent progress in deep learning has led to accurate and efficient generic object detection
networks. Training of highly reliable models depends on large datasets with highly textured …

Target-aware dual adversarial learning and a multi-scenario multi-modality benchmark to fuse infrared and visible for object detection

J Liu, X Fan, Z Huang, G Wu, R Liu… - Proceedings of the …, 2022 - openaccess.thecvf.com
This study addresses the issue of fusing infrared and visible images that appear differently
for object detection. Aiming at generating an image of high visual quality, previous …

U2-Net: Going deeper with nested U-structure for salient object detection

X Qin, Z Zhang, C Huang, M Dehghan, OR Zaiane… - Pattern recognition, 2020 - Elsevier
In this paper, we design a simple yet powerful deep network architecture, U 2-Net, for salient
object detection (SOD). The architecture of our U 2-Net is a two-level nested U-structure. The …

Multi-scale interactive network for salient object detection

Y Pang, X Zhao, L Zhang, H Lu - Proceedings of the IEEE …, 2020 - openaccess.thecvf.com
Deep-learning based salient object detection methods achieve great progress. However, the
variable scale and unknown category of salient objects are great challenges all the time …

Specificity-preserving RGB-D saliency detection

T Zhou, H Fu, G Chen, Y Zhou… - Proceedings of the …, 2021 - openaccess.thecvf.com
RGB-D saliency detection has attracted increasing attention, due to its effectiveness and the
fact that depth cues can now be conveniently captured. Existing works often focus on …