Spatio-temporal transformer networkSpatio-temporal flowSpatio-temporal samplerVideo super-resolutionVideo deblurringState-of-the-art video restoration methods integrate optical flow estimation networks to utilize temporal information. However, these networks typically consider only a pair of consecutive frames ...
On the other hand, the temporal transformer is utilized to model long-range bidirectional temporal dependencies across multiple time steps. (这里吐槽一下,虽然这文章好像是清华的,但这篇摘要有点糟糕。不仅啰嗦,而且说是GNN的变形,可是完全看不出这个结构中有GNN啥事。虽然用transformer去代替RNN是趋势,但这...
Spatio-Temporal Transformer Network for Video Restoration Tae Hyun Kim1,2, Mehdi S. M. Sajjadi1,3, Michael Hirsch1,4† , Bernhard Sch¨olkopf1 1 Max Planck Institute for Intelligent Systems, T¨ubingen, Germany {tkim,msajjadi,bs}@tue.mpg.de 2 Hanyang University, Seoul, Republic of ...
In this article, a novel spatio-temporal transformer graph network is introduced as a means of predicting traffic flow. More precisely, we develop a novel temporal attention module that leverages local context to enhance the stability of long-term predictions in the temporal dimension. We devise a...
Moreover, a Dynamic Spatio-Temporal Graph Transformer Network (DST-GTN) is proposed by capturing Dyn-ST features and other dynamic adjacency relations between intersections. The DST-GTN can model dynamic ST relationships between nodes accurately and refine the representation of global and local ST ...
CVPR 2021 Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking 动机 视觉目标跟踪是计算机视觉中的一项基本任务。尽管最近取得了一些进展,但由于遮挡、变形、外观变化等因素的影响,它仍然是一项具有挑战性的任务。 在视频目标跟踪任务中,现有的跟踪器中被忽略了连续帧之间存在着丰富的...
Kim TH, Sajjadi MS, Hirsch M, Schölkopf B (2018) Spatio-temporal transformer network for video restoration. In: European conference on computer vision. Springer, pp. 111–127 Kisilevich S, Mansmann F, Nanni M, Rinzivillo S (2009) Spatio-temporal clustering. Springer, Boston, pp 855–874...
ROTAN: A Rotation-based Temporal Attention Network for Time-Specific Next POI Recommendation Diffusion-Based Cloud-Edge-Device Collaborative Learning for Next POI Recommendations Urban data Ⅰ 1. Multi-Task Learning for Routing Problem with Cross-Problem Zero-Shot Generalization ...
此文提出了一个基于Transformer名为ST-GRAT的交通预测模型使用self-attention捕捉时空间依赖。 此文对于self-attention做出改进,首先对于spatial attention加上路网信息先验,然后对于spatial和temporal attention都使用sentinel,sentinel可以自适应的选择保留原始信息或者获取新信息。
STN:空间变换网络(Spatial Transformer Network) 。 空间变换器(Spatial Transformers) 一个空间变换器的运作机制可以分为三个部分,如下图所示:1) 本地网络(Localisation Network);2)网格生成器( Grid...,那么 (xsi,ysi)(xis,yis)和(xti,yti)(xit,yit)的对应关系可以写为: 采样器利用采样网格和输入的特征...