Didik Purwanto

Didik Purwanto

Doctor of Philosophy

About

9
Publications
1,222
Reads
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69
Citations

Publications

Publications (9)
Conference Paper
This paper proposes a two-stream network with a novel spatial-temporal multi-head self-attention mechanism for action recognition in extreme low resolution (LR) videos. The new approach first utilizes a super resolution (SR) mechanism to provide better visual information to facilitate the network training. To provide more discriminative spatio-temp...
Article
This letter presents a novel three-stream network for action recognition in extreme low resolution (LR) videos. In contrast to the existing networks, the new network uses the trajectory-spatial network, which is robust against visual distortion, instead of the pose information to complement the two-stream network. Also, the new three-stream network...
Article
This paper presents a convolutional neural network (CNN)-based approach for first-person action recognition with a combination of temporal pooling schemes and the Hilbert-Huang transform (HHT). First, the new approach adaptively selects sub-action intervals, treats each channel of the extracted trajectory pooled CNN features as time series and summ...
Conference Paper
This paper proposes a framework incorporating deep-learned features with the conventional machine learning models within which the objective function is optimized by using quadratic programming or quasi-Newton methods instead of an end-to-end deep learning approach which uses variants of stochastic gradient descent algorithms. A temporal segmentati...
Conference Paper
This paper presents a new discriminative learning framework to associate the relationship between the objects and the words in an image and perform template matching scheme for complex association patterns. The problem is first formulated as a bipartite graph matching problem. Thereafter, structural support vector machine (SVM) is employed to obtai...
Conference Paper
This paper presents a new approach for action recognition in the first-person videos which aggregates both of the shortand long-term trends based on the coefficients of the Hilbert-Huang transform (HHT), a renowned time-frequency analysis tool. In contrast to previous works like Pooled Time Series (PoT), the new scheme can extract the salient featu...

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