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Reliable Visual Perception
[CFAR Rising Star Lecture Series]
Reliable Visual Perception by Gu Jindong
Visual perception plays a crucial role across various domains, including autonomous driving, robotics and computer vision applications.
In this talk, Gu Jindong from the University of Oxford will present his research on reliable visual perception, with specific focus on the robustness of vision models from multiple perspectives: data, model, task and learning paradigm. He will also emphasise the critical factors that impact vision robustness, including potential data perturbations (Natural Variations and Adversarial Attacks), different model architectures (CNN, ViT and CapsNet), the format of tasks (Classification, Segmentation, and Multi-tasks) and different learning paradigms (Standard Learning, Pre-training and Prompting).
Reliable Visual Perception by Gu Jindong
5 Jul 2023 | 4.00pm (Singapore Time)
Visual perception plays a crucial role across various domains, including autonomous driving, robotics and computer vision applications.
In this talk, Gu Jindong from the University of Oxford will present his research on reliable visual perception, with specific focus on the robustness of vision models from multiple perspectives: data, model, task and learning paradigm. He will also emphasise the critical factors that impact vision robustness, including potential data perturbations (Natural Variations and Adversarial Attacks), different model architectures (CNN, ViT and CapsNet), the format of tasks (Classification, Segmentation, and Multi-tasks) and different learning paradigms (Standard Learning, Pre-training and Prompting).
SPEAKER
Gu Jindong
Postdoctoral Researcher
University of Oxford
Postdoctoral Researcher
University of Oxford
Gu Jindong is a postdoctoral researcher at the University of Oxford and is working with Prof. Philip H. S. Torr. Prior to that, he received his Ph.D. from the University of Munich, under the supervision of Prof. Volker Tresp. He has worked and completed his internship at Siemens Technology, Tencent AI Lab, Microsoft Research and Google Research. His research goal is to build Reliable AI by making AI models explainable, robust, and efficient.
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