Co-occurring keywords · papers mentioning both
Papers
Trend-Aware Supervision: On Learning Invariance for Semi-supervised Facial Action Unit Intensity Estimation
AAAI 2024
Bayesian Nonparametric Learning for Point Processes with Spatial Homogeneity: A Spatial Analysis of NBA Shot Locations
ICML 2022
Uniform deconvolution for Poisson Point Processes
JMLR 2022
Dynamic Probabilistic Graph Convolution for Facial Action Unit Intensity Estimation
CVPR 2021
Real-time Tropical Cyclone Intensity Estimation by Handling Temporally Heterogeneous Satellite Data
AAAI 2021
Facial Action Unit Intensity Estimation via Semantic Correspondence Learning with Dynamic Graph Convolution
AAAI 2020
G2RL: Geometry-Guided Representation Learning for Facial Action Unit Intensity Estimation
IJCAI 2020
Context-Aware Feature and Label Fusion for Facial Action Unit Intensity Estimation With Partially Labeled Data
ICCV 2019
Deep Random Splines for Point Process Intensity Estimation of Neural Population Data
NeurIPS 2019
Joint Representation and Estimator Learning for Facial Action Unit Intensity Estimation
CVPR 2019
Thinning for Accelerating the Learning of Point Processes
NeurIPS 2019
Bilateral Ordinal Relevance Multi-Instance Regression for Facial Action Unit Intensity Estimation
CVPR 2018
Discovering Point Lights With Intensity Distance Fields
CVPR 2018
Weakly-Supervised Deep Convolutional Neural Network Learning for Facial Action Unit Intensity Estimation
CVPR 2018
Z-Transforms and its Inference on Partially Observable Point Processes
IJCAI 2018
Fast Bayesian Intensity Estimation for the Permanental Process
ICML 2017
Poisson intensity estimation with reproducing kernels
AISTATS 2017
Copula Ordinal Regression for Joint Estimation of Facial Action Unit Intensity
CVPR 2016
Facial Expression Intensity Estimation Using Ordinal Information
CVPR 2016
Simultaneous Optical Flow and Intensity Estimation From an Event Camera
CVPR 2016
Latent Trees for Estimating Intensity of Facial Action Units
CVPR 2015
Optimality of Poisson Processes Intensity Learning with Gaussian Processes
JMLR 2015