Vocal Bursts Valence Prediction
264 papers with code • 1 benchmarks • 1 datasets
predict the degrees of valence and arousal for the given vocal bursts
Libraries
Use these libraries to find Vocal Bursts Valence Prediction models and implementations
HUME-VB
Most implemented papers
Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net
XingangPan/IBN-Net
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ECCV 2018
IBN-Net carefully integrates Instance Normalization (IN) and Batch Normalization (BN) as building blocks, and can be wrapped into many advanced deep networks to improve their performances.
Two-Stream Convolutional Networks for Action Recognition in Videos
Our architecture is trained and evaluated on the standard video actions benchmarks of UCF-101 and HMDB-51, where it is competitive with the state of the art.
Semantic Style Transfer and Turning Two-Bit Doodles into Fine Artworks
Convolutional neural networks (CNNs) have proven highly effective at image synthesis and style transfer.
PacGAN: The power of two samples in generative adversarial networks
fjxmlzn/PacGAN
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NeurIPS 2018
Generative adversarial networks (GANs) are innovative techniques for learning generative models of complex data distributions from samples.
Towards Good Practices for Very Deep Two-Stream ConvNets
However, for action recognition in videos, the improvement of deep convolutional networks is not so evident.
Light-Head R-CNN: In Defense of Two-Stage Object Detector
More importantly, simply replacing the backbone with a tiny network (e. g, Xception), our Light-Head R-CNN gets 30. 7 mmAP at 102 FPS on COCO, significantly outperforming the single-stage, fast detectors like YOLO and SSD on both speed and accuracy.
Two-pass Discourse Segmentation with Pairing and Global Features
Previous attempts at RST-style discourse segmentation typically adopt features centered on a single token to predict whether to insert a boundary before that token.
MagNet: a Two-Pronged Defense against Adversarial Examples
Trevillie/MagNet
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Different from previous work, MagNet learns to differentiate between normal and adversarial examples by approximating the manifold of normal examples.
Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition
benedekrozemberczki/pytorch_geometric_temporal
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CVPR 2019
In addition, the second-order information (the lengths and directions of bones) of the skeleton data, which is naturally more informative and discriminative for action recognition, is rarely investigated in existing methods.
The Two-Pass Softmax Algorithm
google/XNNPACK
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Performance evaluation demonstrates that on out-of-cache inputs on an Intel Skylake-X processor the new Two-Pass algorithm outperforms the traditional Three-Pass algorithm by up to 28% in AVX512 implementation, and by up to 18% in AVX2 implementation.
