Vocal Bursts Intensity Prediction
763 papers with code • 1 benchmarks • 1 datasets
predict the intensity of 10 categorical emotions
Benchmarks
These leaderboards are used to track progress in Vocal Bursts Intensity Prediction
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Libraries
Use these libraries to find Vocal Bursts Intensity Prediction models and implementations
HUME-VB
Most implemented papers
High Quality Monocular Depth Estimation via Transfer Learning
Accurate depth estimation from images is a fundamental task in many applications including scene understanding and reconstruction.
Deep High-Resolution Representation Learning for Visual Recognition
High-resolution representations are essential for position-sensitive vision problems, such as human pose estimation, semantic segmentation, and object detection.
Deep High-Resolution Representation Learning for Human Pose Estimation
leoxiaobin/deep-high-resolution-net.pytorch
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CVPR 2019
We start from a high-resolution subnetwork as the first stage, gradually add high-to-low resolution subnetworks one by one to form more stages, and connect the mutli-resolution subnetworks in parallel.
High-Resolution Representations for Labeling Pixels and Regions
leoxiaobin/deep-high-resolution-net.pytorch
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The proposed approach achieves superior results to existing single-model networks on COCO object detection.
Large Scale GAN Training for High Fidelity Natural Image Synthesis
ajbrock/BigGAN-PyTorch
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ICLR 2019
Despite recent progress in generative image modeling, successfully generating high-resolution, diverse samples from complex datasets such as ImageNet remains an elusive goal.
High-Resolution Image Synthesis with Latent Diffusion Models
compvis/stable-diffusion
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CVPR 2022
By decomposing the image formation process into a sequential application of denoising autoencoders, diffusion models (DMs) achieve state-of-the-art synthesis results on image data and beyond.
High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs
NVIDIA/pix2pixHD
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CVPR 2018
We present a new method for synthesizing high-resolution photo-realistic images from semantic label maps using conditional generative adversarial networks (conditional GANs).
High-Performance Large-Scale Image Recognition Without Normalization
deepmind/deepmind-research
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Batch normalization is a key component of most image classification models, but it has many undesirable properties stemming from its dependence on the batch size and interactions between examples.
High-Dimensional Continuous Control Using Generalized Advantage Estimation
labmlai/annotated_deep_learning_paper_implementations
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Policy gradient methods are an appealing approach in reinforcement learning because they directly optimize the cumulative reward and can straightforwardly be used with nonlinear function approximators such as neural networks.
ICNet for Real-Time Semantic Segmentation on High-Resolution Images
We focus on the challenging task of real-time semantic segmentation in this paper.
