To reduce the number of MACs in CNNs, we propose a value\nprediction method that exploits the spatial correlation of zero-valued\nactivations within the CNN output feature maps, thereby saving convolution\noperations. Our method reduces the number of MAC operations by 30.4%, averaged\non three...
Danelljan M, Bhat G, Khan FS, Felsberg M (2017) ECO: efficient convolution operators for tracking. In: IEEE conference on computer vision and pattern recognition, pp 6931–6939 Xu T, Feng ZH, Wu XJ, Kittler J (2019) Learning adaptive discriminative correlation filters via temporal consistency...
Noted that we leverage the trainable parameters γ∈ RC in GN layers as a way to measure the variance of spatial pixels for each batch and channel. The richer spatial infor- mation reflects more variation in spatial pixels contributing to a larger γ. The no...
By providing semantic information concerning action execution, the semantic adjacency matrix enables the model to better understand the intrinsic correlations and meanings of actions. As shown in Figure 3, with the FastDTW algorithm, point a of a series M is correlated with point z of another ...
From a signal processing perspective, this detection process can be efficiently posed as a correlation/ convolution betwee... HK Galoogahi,T Sim,S Lucey 被引量: 0发表: 2013年 CMOS implementation of image deconvolution and mean field annealing w.e report the physic~ i~pleme.ntation of a ...
We have found an efficient way to treat statistical correlations in the shapes and orientations of the communicating cavities, and also obtained a ... M Jakobsen,TA Johansen,C Mccann - 《Journal of Applied Geophysics》 被引量: 112发表: 2003年 Three‐Dimensional Magnetohydrodynamic Modeling of ...
(2016). Beyond correlation filters: Learning continuous convolution operators for visual tracking. In Proceedings of the European conference on computer vision (pp. 472–488). Springer. Dinh, T. B., Vo, N., & Medioni, G. (2011). Context tracker: Exploring supporters and distracters in ...
spatial correlation structure across tissue locations, thus preserving the neighboring similarity of the original data in the low-dimensional manifold. The low-dimensional components obtained from SpatialPCA contain valuable spatial correlation information and can be directly paired with existing computational ...
with 64 filters of dilation rates 3, 5 and 7, respectively, are used. The combined feature map,Fin, is subjected to atrous convolution and the resultant enhanced feature map of size 32×32×256, is given to a sequential combination of channel attention (CA) network and spatial attention (...
It can fully utilize channel and spatial correlations simultaneously to extract global information, especially under difficult conditions. 2. A powerful, lightweight design. To avoid dimensionality reduction, we recommend 1D and 2D convolutions across channels and spaces. 3. Numerous experiments. ...