Applications in Computer Vision

Object Detection/Semantic Segmentation (6 papers)

Z. Zhao, P. Zheng, S. Xu, X. Wu, "Object Detection with Deep Learning: A Review", Preprint, July 2018.

R. Girshick, J. Donahue, T. Darrell, J. Malik,” Rich feature hierarchies for accurate object detection and semantic segmentation”, IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2014, 2014.

R. Girshick, “Fast R-CNN”, IEEE International Conference on Computer Vision, ICCV 2015, 2015.

S. Ren, K. He, R. Girshick, J. Sun, “Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 39, pages 1137-1149, 2017.

J. Dai, Y. Li, K. He, J. Sun, “R-FCN: Object Detection via Region-based Fully Convolutional Networks”, NIPS 2016, 2016.

T. Cane, J. Ferryman, “Evaluating deep semantic segmentation networks for object detection in maritime surveillance”, IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2018, pages 1-6, 2018.

X. You, H. Liu, T. Wang, "Object Detection by Crossing Relational Reasoning based on Graph Neural Network", Machine Vision and Applications, Volume 33, 2022.

Video Object Segmentation (7 papers)

Y. Hu, J. Huang, A. Schwing, “MaskRNN: Instance Level Video Object Segmentation”, NIPS 2017, 2017.

V. Goel, J. Weng, P. Poupart, “Unsupervised Video Object Segmentation for Deep Reinforcement Learning”, Preprint, 2018.

H. Xiao, J. Feng, G. Lin, Y. Liu, M. Zhang, “MoNet: Deep Motion Exploitation for Video Object Segmentation”, CVPR 2018, pages 1140-1148, 2018.

J. Yoon, F. Rameau, J. Kim, S. Lee, S. Shin, I. S. Kweon, “Pixel-level matching for video object segmen-tation using convolutional neural networks”, ICCV 2017, 2017.

W. Jang, C. Kim, “Online video object segmentation via convolutional trident network”, CVPR 2017, 2017.

J. Sasikumar, “Investigating the Application of Deep Convolutional Neural Networks in Semi-supervised Video Object Segmentation”, Master Science Thesis, Technological University Dublin, 2018.

D. Li, M. Jiang, Y. Fang, Y. Huang, C. Zhao, “Deep video foreground target extraction with complex scenes, IEEE International Conference on Sensor Networks and Signal Processing, SNSP 2018, pages 440-445, 2018.

Video Anomaly Detection (1 paper)

K. Gunale, P. Mukherji, "Deep Learning with a Spatiotemporal Descriptor of Appearance and Motion Estimation for Video Anomaly Detection", MDPI Journal of Imaging, 2018.

Person Detection and Tracking (1 paper)

A. Brunettia, D. Buongiorno, G. Trotta, V. Bevilacqua, 3Computer vision and deep learning techniques for pedestrian detection and tracking: A survey3, Neurocomputing, July 2018.

Person Re-Identification (3 papers)

D. Wu et al., “Deep learning-based methods for person re-identification: A comprehensive review”, Neurocomputing, February 2019.

B. Lavi, M. Serj, I. Ullah, “Survey on Deep Learning Techniques for Person Re-Identification Task”, Neurocomputing, 2018.

A. Rahimpour, H. Qi, “Attention-based Few-Shot Person Re-identification using Meta Learning”, Preprint, 2018.

Dim Small Target Detection (1 paper)

J. Bai, H. Zhang, Z. Li, “The Generalized Detection Method for the Dim Small Targets by Faster R-CNN Integrated with GAN”, IEEE International Conference on Communication and Information Systems, ICCIS 2018, pages 1–5, 2018.

Face Detection (1 paper)

T. Pham, "Semantic Convolutional Features for Face Detection", Machine Vision and Applications, Volume 33, 2022.

Face Alignment (2 papers)

F. Chang, A. Tran, T. Hassner, I. Masi, R. Nevatia, G. Medioni, “Deep, Landmark-Free FAME: Face Alignment, Modeling, and Expression Estimation”, International Journal of Computer Vision, 2019.

F. Chang, A. Tran, T. Hassner, I. Masi, R. Nevatia, G. Medioni, “FacePoseNet: Making a Case for Landmark-Free Face Alignment, Analysis and Modeling of Faces and Gestures”, ICCVW 2017, 2017.

Motion Recognition (1 paper)

S. Daraei, "Deep Learning for Motion Recognition", PhD Thesis, University of Pittsburgh, 2021.

Face Recognition (1 paper)

M. Wang, W. Deng, "Deep Face Recognition: A Survey", Preprint, February 2019.

Action Recognition (2 papers)

G. Yao, T. Lei, J. Zhong, “A Review of Convolutional-Neural-Network-based Action Recognition”, Pattern Recognition Letters, pages 14–22, 2019.

J. Wang, Y.Chen, S. Hao, X. Peng, L. Hu, “Deep Learning for Sensor-based Activity Recognition: A Survey”, Pattern Recognition Letters, Volume 119, pages 3-11, March 2019.

Intelligent Transportation System (3 papers)

Q. Wang, J. Gao, Y. Yuan, “Embedding structured contour and location prior in siamesed fully convolutional networks for road detection”, IEEE Transactions on Intelligent Transportation Systems, pages 230–241, January 2018.

Q.Wang, J.Wan, X. Li, “Robust Hierarchical Deep Learning for Vehicular Management”, IEEE Transactions on Vehicular Technology, 2018.

Y. Yuan, a. Q. W. Z. Xiong, “ACM: Adaptive Cross-Modal Graph Convolutional Neural Networks for RGB-D Scene Recognition”, AAAI Conference on Artificial Intelligence, AAAI 2019, 2019.

Remote Sensing (2 papers)

Q. Wang, S. Liu, J. Chanussot, X. Li, “Scene classification with recurrent attention of VHR remote sensing images”, IEEE Transactions on Geoscience and Remote Sensing, 2018.

Q. Wang, Z. Yuan, Q. Du, X. Li, “GETNET: A General End-to-End 2-D CNN Framework for Hyperspectral Image Change Detection”, IEEE Transactions on Geoscience and Remote Sensing, pages 3–13, January 2019.