CVPR 2022 | 一键解锁微软亚洲研究院计算机视觉领域前沿进展!
编者按：国际计算机视觉与模式识别会议（CVPR）是人工智能领域最具学术影响力的顶级会议之一。微软亚洲研究院也在4月成功举办了 CVPR 2022 论文分享会。今天，我们为大家精选了8篇微软亚洲研究院被 CVPR 2022 收录的优秀论文，带你探索计算机视觉领域的热点前沿！欢迎感兴趣的读者阅读论文原文。 论文链接：https://arxiv.org/abs/2203.09208 视频复原任务非常依赖...
In the news | Microsoft On the Issues
Defending Ukraine: Early Lessons from the Cyber War
Editor’s note: Today Microsoft published a new intelligence report, Defending Ukraine: Early Lessons from the Cyber War. This report represents research conducted by Microsoft’s threat intelligence and data science teams with the goal of sharpening our understanding of the threat landscape in…
Awards | Doctoral Dissertation
Li Zhong’s Outstanding Doctoral Dissertation Award, Peking University
Li Zhong was recognized as one of Peking University's Outstanding Doctoral Dissertations in 2022 in Computational Mathematics for the paper, "Machine Learning Theory of Dynamical Systems".
Swin Transformer supports 3-billion-parameter vision models that can train with higher-resolution images for greater task applicability
| Han Hu and Baining Guo
Early last year, our research team from the Visual Computing Group introduced Swin Transformer, a Transformer-based general-purpose computer vision architecture that for the first time beat convolutional neural networks on the important vision benchmark of COCO object detection (opens in…
In the news | New York Times
Microsoft Plans to Eliminate Face Analysis Tools in Push for ‘Responsible A.I.’
In the news | Microsoft Innovation
Tech Minutes: Swin Transformer
Learn how Swin Transformer surpasses previously dominant CNN (convolutional neural network) architectures in computer vision. Presented by Han Hu, Principal Researcher and Research Manager from Microsoft Research Asia.
As a top international academic conference in the field of natural language processing, ACL attracts paper submissions and conference participation from a large number of scholars every year. This year's ACL conference was held from May 22nd to May 27th.…
夏炎：做科学研究与技术应用的“摆渡人”
编者按：科学研究与技术创新的过程总是充满了不确定性，科研人员无法提前计算创新的周期，也无法预料每个灵感所带来的最终结果。若想将一项研究成果落地并通过产品化的方式让更多人感受到前沿技术所带来的便利，研究工程师的参与尤为重要，他们需要全面掌握终端用户的需求，深入了解技术应用的深度与广度，打通各个环节的流程，有效地将算法模型与产品应用连接起来。然而知易行难，这一过程中的艰辛与技术落地时的成就感也只有亲身...