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直播回放 Self-Adaptive Visual Learning 自适应视觉学习
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1.Topic: Self-Adaptive Visual Learning
演讲题目:自适应视觉学习
2. Language: English
演讲语言:英文
3. Speaker: Yang Wang is an associate professor in the Department of Computer Science, University of Manitoba. He is also currently on leave and working as the Chief Scientist in Computer Vision, Noah's Ark Lab, Huawei Technologies Canada. He did his PhD from Simon Fraser University, MSc from University of Alberta, and BEng from Harbin Institute of Technology. Before joining UManitoba, he worked as a NSERC postdoc at the University of Illinois at Urbana-Champaign.
演讲嘉宾:Yang Wang, 西蒙·弗雷泽大学博士学位、阿尔伯塔大学硕士、哈尔滨工业大学学士。现为曼尼托巴大学计算机科学系副教授,华为技术加拿大公司诺亚方舟实验室计算机视觉首席专家。在加入曼尼托巴大学之前,曾在伊利诺伊大学香槟分校任NSERC博士后。
4. Abstract: There have been significant advances in computer vision in the past few years. Despite of the success, current computer vision systems are still hard to use or deploy in many real-world scenarios. In particular, current computer vision systems usually learn a generic model. But in real world applications, a single generic model is often not powerful enough to handle the diverse scenarios. In this talk, I will introduce some of our recent work on self-adaptive visual learning. Instead of learning and deploying one generic model, our goal is to learn a model that can effectively adapt itself to different environments during testing. I will present applications from several computer visions, such as crowd counting, anomaly detection, personalized highlight detection, etc.
演讲摘要:在过去的几年中,计算机视觉实现了很大的进步。尽管如此,将计算机视觉系统直接应用于现实世界的诸多场景中仍然很难实现。特别是当前的计算机视觉系统通常学习的是一个通用的模型,然而在现实的实际应用中,单一的通用模型通常不足以处理不同场景中出现的问题。我们的目标是研究出一个可以在测试中不断适应变化的环境的模型,而不仅仅是学习或扩展一个通用模型。此次讲座中,Yang Wang博士将为大家介绍近期在计算机自适应视觉学习方面的工作进展,并通过人群计数、异常检测、个性化高光检测等案例为大家展示一下计算机视觉在当下的应用情况。


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