in british newspapers, spanish newspapers, i tell you newspapers and so forth. in the united states wide circulation newspapers printed very full first-hand accounts. ukrainian americans and other visitors, mostly discounted as often appearing at right wing journals. the times longtime man in moscow was walter duranty. a propagandist and apologist for the 1970 convolution in russia. he reported otherwise. indeed, the times were proud of their man in moscow in 1932 he was awarded a pulitzer prize for a series of articles in the new york times that covered up the atrocities. from 1932 until 33 writing news columnist for the times not only deny the fact that the catastrophic famine was taking place in the ukraine, but censoring the role in the
in british newspapers, spanish newspapers, i tell you newspapers and so forth. in the united states wide circulation newspapers printed very full first-hand accounts. ukrainian americans and other visitors, mostly discounted as often appearing at right wing journals. the times longtime man in moscow was walter duranty. a propagandist and apologist for the 1970 convolution in russia. he reported otherwise. indeed, the times were proud of their man in moscow in 1932 he was awarded a pulitzer prize for a series of articles in the new york times that covered up the atrocities. from 1932 until 33 writing news columnist for the times not only deny the fact that the catastrophic famine was taking place in the ukraine, but censoring the role in the
This paper proposes a new graph convolutional operator called central difference graph convolution (CDGC) for skeleton based action recognition. It is not only able to aggregate node information like a vanilla graph convolutional operation but also gradient information. Without introducing any additional parameters, CDGC can replace vanilla graph convolution in any existing Graph Convolutional Networks (GCNs). In addition, an accelerated version of the CDGC is developed which greatly improves the speed of training. Experiments on two popular large-scale datasets NTU RGB+D 60 & 120 have demonstrated the efficacy of the proposed CDGC. Code is available at https://github.com/iesymiao/CD-GCN.
In video coding, it is a challenge to deal with scenes with complex motions, such as rotation and zooming. Although affine motion compensation (AMC) is employed in Versatile Video Coding (VVC), it is still difficult to handle non-translational motions due to the adopted hand-craft block-based motion compensation. In this paper, we propose a deep affine motion compensation network (DAMC-Net) for inter prediction in video coding to effectively improve the prediction accuracy. To the best of our knowledge, our work is the first attempt to deal with the deformable motion compensation based on CNN in VVC. Specifically, a deformable motion-compensated prediction (DMCP) module is proposed to compensate the current encoding block through a learnable way to estimate accurate motion fields. Meanwhile, the spatial neighboring information and the temporal reference block as well as the initial motion field are fully exploited. By effectively fusing the multi-channel feature maps from DMCP, an atte
Optical methods of super-resolution microscopy, such as confocal microscopy, structured illumination, nonlinear microscopy, and image scanning microscopy are reviewed. These methods avoid strong invasive interaction with a sample, allowing the observation of delicate biological samples. The meaning of resolution and the basic principles and different approaches to superresolution are discussed.