Fetching the paper…
Reading the bibliography…
Computer Vision has played a major role in Intelligent Transportation Systems (ITS) and traffic surveillance.
Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography
Fischler, M. A. & Bolles, R. C · 1981
Earlier work this paper cites.
Seeded region growing
Adams, R. & Bischof, L · 1994
Earlier work this paper cites.
Object recognition from local scale-invariant features
Lowe, D · 1999
Earlier work this paper cites.
A survey on visual surveillance of object motion and behaviors
Hu, W., Tan, T., Wang, L. & Maybank, S · 2004
Earlier work this paper cites.
Robust techniques for background subtraction in urban traffic video
Cheung, S.-c. S. & Kamath, C · 2004
Earlier work this paper cites.
Moving vehicle detection for automatic traffic monitoring
Zhou, J., Gao, D. & Zhang, D · 2007
Earlier work this paper cites.
Camera calibration from orthogonally projected coordinates with noisy-ransac
Kim, Z · 2009
Earlier work this paper cites.
Asift: An algorithm for fully affine invariant comparison
Yu, G. & Morel, J.-M · 2011
Earlier work this paper cites.
Video based vehicle detection and its application in intelligent transportation systems
Chintalacheruvu, N., Muthukumar, V. et al · 2012
Earlier work this paper cites.
Vision-based vehicle detection system with consideration of the detecting location
Cheon, M., Lee, W., Yoon, C. & Park, M · 2012
Earlier work this paper cites.
Vehicle tracking by simultaneous detection and viewpoint estimation
Guerrero-Gomez-Olmedo, R., Lopez-Sastre, R. J., Maldonado-Bascon, S. & Fernandez-Caballero, A · 2013
Earlier work this paper cites.
Multimodal inverse perspective mapping
Oliveira, M., Santos, V. & Sappa, A. D · 2015
Earlier work this paper cites.
Robust vehicle detection and distance estimation under challenging lighting conditions
Rezaei, M., Terauchi, M. & Klette, R · 2015
Earlier work this paper cites.
Fully automatic roadside camera calibration for traffic surveillance
Dubská, M., Herout, A., Juránek, R. & Sochor, J · 2015
Earlier work this paper cites.
Microsoft coco: Common objects in context (2015)
Lin, T.-Y. et al · 2015
Earlier work this paper cites.
Automated traffic monitoring system using computer vision
Poddar, M., Giridhar, M., Prabhu, A. S., Umadevi, V. et al · 2016
Earlier work this paper cites.
Ssd: Single shot multibox detector
Liu, W. et al · 2016
Earlier work this paper cites.
Context-aware fusion of rgb and thermal imagery for traffic monitoring
Alldieck, T., Bahnsen, C. H. & Moeslund, T. B · 2016
Earlier work this paper cites.
Deep3d: Fully automatic 2d-to-3d video conversion with deep convolutional neural networks
Xie, J., Girshick, R. & Farhadi, A · 2016
Earlier work this paper cites.
Simple online and realtime tracking
Bewley, A., Ge, Z., Ott, L., Ramos, F. & Upcroft, B · 2016
Earlier work this paper cites.
Computer vision for driver assistance
Rezaei, M. & Klette, R · 2017
Cited alongside, same era.
Traffic surveillance camera calibration by 3D model bounding box alignment for accurate vehicle speed measurement
Sochor, J., Juránek, R. & Herout, A · 2017
Cited alongside, same era.
Focal loss for dense object detection
Lin, T.-Y., Goyal, P., Girshick, R., He, K. & Dollár, P · 2017
Cited alongside, same era.
Simple online and realtime tracking with a deep association metric
Wojke, N., Bewley, A. & Paulus, D · 2017
Cited alongside, same era.
Resnet-based vehicle classification and localization in traffic surveillance systems
Jung, H. et al · 2017
Cited alongside, same era.
Efficient scene layout aware object detection for traffic surveillance
Wang, T., He, X., Su, S. & Guan, Y · 2017
Cited alongside, same era.
Monocular depth estimation: A survey
Bhoi, A · 2019
Later among the works it cites.
3d vehicle model-based ptz camera auto-calibration for smart global village
Song, H. et al · 2019
Later among the works it cites.
Towards accurate high resolution satellite image semantic segmentation
Wu, M., Zhang, C., Liu, J., Zhou, L. & Li, X · 2019
Later among the works it cites.
Visual traffic surveillance: A concise survey
Mondal, A., Dutta, A., Dey, N. & Sen, S · 2020
Later among the works it cites.
Pedestrian detection and tracking in video surveillance system: Issues, comprehensive review, and challenges
Gawande, U., Hajari, K. & Golhar, Y · 2020
Later among the works it cites.
A multi-class multi-movement vehicle counting framework for traffic analysis in complex areas using cctv systems
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Smart cities: Challenges and opportunities
Nambiar, R., Shroff, R. & Handy, S · 2018
Cited alongside, same era.
Fast and accurate vanishing point detection and its application in inverse perspective mapping of structured road
Yang, W., Fang, B. & Tang, Y. Y · 2018
Cited alongside, same era.
Computer vision and deep learning techniques for pedestrian detection and tracking: A survey
Brunetti, A., Buongiorno, D., Trotta, G. F. & Bevilacqua, V · 2018
Cited alongside, same era.
Detection and classification of vehicles for traffic video analytics
Arinaldi, A., Pradana, J. A. & Gurusinga, A. A · 2018
Cited alongside, same era.
Mio-tcd: A new benchmark dataset for vehicle classification and localization
Luo, Z. et al · 2018
Cited alongside, same era.
Path aggregation network for instance segmentation
Liu, S., Qi, L., Qin, H., Shi, J. & Jia, J · 2018
Cited alongside, same era.
Bui, K.-H. N., Yi, H. & Cho, J · 2020
Later among the works it cites.
Artificial intelligence-enabled traffic monitoring system
Mandal, V., Mussah, A. R., Jin, P. & Adu-Gyamfi, Y · 2020
Later among the works it cites.
Vehicle Tracking and Speed Estimation From Roadside Lidar
Zhang, J., Xiao, W., Coifman, B. & Mills, J. P · 2020
Later among the works it cites.
Automatic detection and classification of road, car, and pedestrian using binocular cameras in traffic scenes with a common framework
Song, Y., Yao, J., Ju, Y., Jiang, Y. & Du, K · 2020
Later among the works it cites.
Cspnet: A new backbone that can enhance learning capability of cnn
Wang, C.-Y. et al · 2020
Later among the works it cites.
Dc-spp-yolo: Dense connection and spatial pyramid pooling based yolo for object detection
Huang, Z. et al · 2020
Later among the works it cites.
Distance-iou loss: Faster and better learning for bounding box regression
Zheng, Z. et al · 2020
Later among the works it cites.
UA-DETRAC: A new benchmark and protocol for multi-object detection and tracking
Wen, L. et al · 2020
Later among the works it cites.
A super-learner ensemble of deep networks for vehicle-type classification
Hedeya, M. A., Eid, A. H. & Abdel-Kader, R. F · 2020
Later among the works it cites.
Deepsocial: Social distancing monitoring and infection risk assessment in covid-19 pandemic
Rezaei, M. & Azarmi, M · 2020
Later among the works it cites.
Surveilling surveillance: Estimating the prevalence of surveillance cameras with street view data
Sheng, H., Yao, K. & Goel, S · 2021
Closest in time.
Towards an end-to-end framework of cctv-based urban traffic volume detection and prediction
Peppa, M. V. et al · 2021
Closest in time.
Point-cloud based 3d object detection and classification methods for self-driving applications: A survey and taxonomy
Fernandes, D. et al · 2021
Closest in time.
Rgb-d salient object detection: A survey
Zhou, T., Fan, D.-P., Cheng, M.-M., Shen, J. & Shao, L · 2021
Closest in time.
ultralytics/yolov5: v5.0 - YOLOv5-P6 1280 models, AWS, Supervise.ly and YouTube integrations, DOI: 10.5281/zenodo.4679653 (2021)
Jocher, G. et al · 2021
Closest in time.