Yang worked as a senior research scientist at the Honda Research Institute in Mountain View,California.[6] He joined UC Merced in 2008. Since 2018,he has been a research scientist at Google DeepMind.[2][7] He previously chaired the IEEE International Conference on Computer Vision (ICCV)[8] and the Asian Conference on Computer Vision (ACCV).[9]
Research
Much of Yang's research has explored intelligent systems such as AI,machine learning,computer vision,and robotics. In a paper published in 2013,Yang assessed online object tracking algorithms through large-scale experiments,identifying methods,benchmarking performance,and highlighting key factors influencing tracking accuracy across different scenarios.[10] He also presented a graph-based manifold ranking approach for saliency detection,integrating foreground and background cues,and benchmark dataset evaluation.[11]
Yang has been named a highly cited researcher from 2018 to 2024.[12]
2025 –Test-of-Time Award,IEEE Winter Conference on Applications of Computer Vision (WACV)[21]
Bibliography
Books
Yang, Ming-Hsuan; Ahuja, Narendra (2012). Face Detection and Gesture Recognition for Human-Computer Interaction. Kluwer Academic Publishers. ISBN9781461514237.
Selected articles
Yang, M.-H.; Kriegman, D. J.; Ahuja, N. (2002). "Detecting faces in images: A survey". IEEE Transactions on Pattern Analysis and Machine Intelligence. 24 (1): 34–58. doi:10.1109/34.982883.
Ross, D. A.; Lim, J.; Lin, R. S.; Yang, M.-H. (2008). "Incremental learning for robust visual tracking". International Journal of Computer Vision. 77 (1–3): 125–141. doi:10.1007/s11263-007-0075-7.
Wu, Y.; Lim, J.; Yang, M.-H. (2013). "Online object tracking: A benchmark". Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp.2411–2418. doi:10.1109/CVPR.2013.312.
Lai, W. S.; Huang, J. B.; Ahuja, N.; Yang, M.-H. (2017). "Deep Laplacian pyramid networks for fast and accurate super-resolution". Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp.624–632. doi:10.1109/CVPR.2017.618.
Gao, S. H.; Cheng, M. M.; Zhao, K.; Zhang, X. Y.; Yang, M.-H.; Torr, P. (2019). "Res2Net: A new multi-scale backbone architecture". IEEE Transactions on Pattern Analysis and Machine Intelligence. 43 (2): 652–662. arXiv:1904.01169. doi:10.1109/TPAMI.2019.2938758. PMID31484108.
This page is based on this Wikipedia article Text is available under the CC BY-SA 4.0 license; additional terms may apply. Images, videos and audio are available under their respective licenses.
