Update

Dr. Xinyu Yang

Postdoc

Xinyu Yang is a Senior Research Associate at Lancaster University, specializing in the development of innovative AI model training and learning technologies. With a background in Machine Learning, Deep Learning, and Computer Vision, Xinyu's research focuses on reducing the need for manual labeling in various computer vision tasks. He holds a PhD in Computer Vision from the University of Bristol, where his research concentrated on the application of AI to animal-related fields. His research interests include biometrics, image synthesis, and advanced learning paradigms such as self/weakly-supervised and zero-shot learning, with relevant work published in several conferences and journals.

Email: x.yang28 (at) lancaster.ac.uk

Office: InfoLab21 A25, School of Computing and Communications, Lancaster University

Research

Weakly Supervised Co-training with Swapping Assignments for Semantic Segmentation
Xinyu Yang, Hossein Rahmani, Sue Black, Bryan M. Williams
ECCV, 2024
[Webpage] [arXiv] [Code] [pdf]
Dynamic Curriculum Learning for Great Ape Detection in the Wild
Xinyu Yang, Tilo Burghardt, Majid Mirmehdi
IJCV, 2023
[Webpage] [arXiv] [Code] [pdf]
Back to the Future: Cycle Encoding Prediction for Self-supervised Video Representation Learning
Xinyu Yang, Majid Mirmehdi, Tilo Burghardt
BMVA British Machine Vision Conference, 2021
[Webpage] [arXiv] [Code] [pdf]
Great Ape Detection in Challenging Jungle Camera Trap Footage via Attention-Based Spatial and Temporal Feature Blending
Xinyu Yang, Majid Mirmehdi, Tilo Burghart
Computer Vision for Wildlife Conservation on ICCV, 2019
[Webpage] [arXiv] [Code] [pdf]

Misc.

Teaching

Reviewer