Vocal Bursts Intensity Prediction
765 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
Generating Diverse High-Fidelity Images with VQ-VAE-2
deepmind/sonnet
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NeurIPS 2019
We explore the use of Vector Quantized Variational AutoEncoder (VQ-VAE) models for large scale image generation.
Lite-HRNet: A Lightweight High-Resolution Network
HRNet/Lite-HRNet
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CVPR 2021
We introduce a lightweight unit, conditional channel weighting, to replace costly pointwise (1x1) convolutions in shuffle blocks.
RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
guosheng/refinenet
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CVPR 2017
Recently, very deep convolutional neural networks (CNNs) have shown outstanding performance in object recognition and have also been the first choice for dense classification problems such as semantic segmentation.
Taming Transformers for High-Resolution Image Synthesis
CompVis/taming-transformers
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CVPR 2021
We demonstrate how combining the effectiveness of the inductive bias of CNNs with the expressivity of transformers enables them to model and thereby synthesize high-resolution images.
Restormer: Efficient Transformer for High-Resolution Image Restoration
Since convolutional neural networks (CNNs) perform well at learning generalizable image priors from large-scale data, these models have been extensively applied to image restoration and related tasks.
FaceBoxes: A CPU Real-time Face Detector with High Accuracy
The MSCL aims at enriching the receptive fields and discretizing anchors over different layers to handle faces of various scales.
FaceShifter: Towards High Fidelity And Occlusion Aware Face Swapping
We propose a novel attributes encoder for extracting multi-level target face attributes, and a new generator with carefully designed Adaptive Attentional Denormalization (AAD) layers to adaptively integrate the identity and the attributes for face synthesis.
High-Speed Tracking with Kernelized Correlation Filters
Interestingly, for linear regression our formulation is equivalent to a correlation filter, used by some of the fastest competitive trackers.
Breaking the Softmax Bottleneck: A High-Rank RNN Language Model
We formulate language modeling as a matrix factorization problem, and show that the expressiveness of Softmax-based models (including the majority of neural language models) is limited by a Softmax bottleneck.
Cascade R-CNN: Delving into High Quality Object Detection
zhaoweicai/cascade-rcnn
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CVPR 2018
In object detection, an intersection over union (IoU) threshold is required to define positives and negatives.
