The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Siwei Lyu sits on this spectrum.
This scientist: 195 publications — 44th percentile
44% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 991 publications or more.
The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Siwei Lyu sits on this spectrum.
This scientist: 61 D-Index — 79th percentile
79% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 131 D-Index or more.
Siwei Lyu is affiliated with the University at Buffalo, State University of New York in the United States. Their research has primarily focused on areas within computer science, especially in computer vision and pattern recognition. Lyu's scholarly contributions encompass topics such as generative adversarial networks and image synthesis, digital media forensic detection, face recognition and analysis, adversarial robustness in machine learning, anomaly detection techniques and applications, advanced neural network applications, and advanced image processing techniques.
The scientist has authored numerous papers, with significant publications including:
Lyu has collaborated frequently with several researchers, including Shu Hu, Yuezun Li, Ming-Ching Chang, Honggang Qi, and Xin Wang. These collaborations have resulted in multiple co-authored works.
Their publications are often found in leading venues such as arXiv (Cornell University), Computer Vision and Image Understanding, the IEEE International Conference on Image Processing (ICIP), the Proceedings of the AAAI Conference on Artificial Intelligence, and IEEE Transactions on Multimedia.
The academic fields covered by Lyu's work include:
Within this broader field, the scientist focuses on subfields such as:
Siwei Lyu's work addresses methods and challenges related to image and video analysis, forensic detection of synthetic media, and the application of adversarial training techniques in machine learning. The research efforts also include creating benchmarks and protocols for multi-object detection and tracking, as well as developing models for high-quality image inpainting.
Matej Kristan;Aleš Leonardis;Jiři Matas;Michael Felsberg
Matej Kristan;Ales Leonardis;Jiri Matas;Michael Felsberg
Matej Kristan;Jiri Matas;Ale Leonardis;Michael Felsberg
Yuezun Li;Xin Yang;Pu Sun;Honggang Qi
Xin Yang;Yuezun Li;Siwei Lyu
Yuezun Li;Ming-Ching Chang;Siwei Lyu
Siwei Lyu;Hany Farid
Yuezun Li;Siwei Lyu
Longyin Wen;Dawei Du;Zhaowei Cai;Zhen Lei
S. Lyu;H. Farid
Xunyu Pan;Siwei Lyu
S. Lyu;H. Farid
Hany Farid;Siwei Lyu
Wenbo Li;Pengchuan Zhang;Lei Zhang;Qiuyuan Huang
Lipeng Ke;Ming-Ching Chang;Honggang Qi;Siwei Lyu
Siwei Lyu;Hany Farid
Siwei Lyu;Daniel N. Rockmore;Hany Farid
Siwei Lyu;Xunyu Pan;Xing Zhang
Yuezun Li;Ming-Ching Chang;Siwei Lyu
Xunyu Pan;Siwei Lyu
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