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Found 7 papers, 0 papers with code
Self-Reorganizing and Rejuvenating CNNs for Increasing Model Capacity Utilization
In this paper, we propose self-reorganizing and rejuvenating convolutional neural networks; a biologically inspired method for improving the computational resource utilization of neural networks.
Mode Variational LSTM Robust to Unseen Modes of Variation: Application to Facial Expression Recognition
The effectiveness of the proposed mode variational LSTM is verified using the facial expression recognition task.
Facial Expression Recognition
Facial Expression Recognition (FER)
Measurement of exceptional motion in VR video contents for VR sickness assessment using deep convolutional autoencoder
This paper proposes a new objective metric of exceptional motion in VR video contents for VR sickness assessment.
Dynamics Transfer GAN: Generating Video by Transferring Arbitrary Temporal Dynamics from a Source Video to a Single Target Image
The spatial constructs of a generated video sequence are acquired from the target image.
Learning Spatio-temporal Features with Partial Expression Sequences for on-the-Fly Prediction
At test time, most spatio-temporal encoding methods assume that a temporally segmented sequence is fed to a learned model, which could require the prediction to wait until the full sequence is available to an auxiliary task that performs the temporal segmentation.
Differential Generative Adversarial Networks: Synthesizing Non-linear Facial Variations with Limited Number of Training Data
through a generative model is helpful in addressing the lack of training data.
Convolution with Logarithmic Filter Groups for Efficient Shallow CNN
Our classification results on Multi-PIE dataset for facial expression recognition and CIFAR-10 dataset for object classification reveal that the compact CNN with the proposed logarithmic filter grouping scheme outperforms the same network with the uniform filter grouping in terms of accuracy and parameter efficiency.
