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Found 23 papers, 11 papers with code
A Generative Multi-Resolution Pyramid and Normal-Conditioning 3D Cloth Draping
RGB cloth generation has been deeply studied in the related literature, however, 3D garment generation remains an open problem.
Machine learning-based characterization of hydrochar from biomass: Implications for sustainable energy and material production
Hydrothermal carbonization (HTC) is a process that converts biomass into versatile hydrochar without the need for prior drying.
Blowing in the Wind: CycleNet for Human Cinemagraphs from Still Images
We investigate the problem in the context of dressed humans under the wind.
Neural Cloth Simulation
Here, we propose the first methodology able to learn realistic cloth dynamics unsupervisedly, and henceforth, a general formulation for neural cloth simulation.
Predicting the generalization gap in neural networks using topological data analysis
Understanding how neural networks generalize on unseen data is crucial for designing more robust and reliable models.
Winning solutions and post-challenge analyses of the ChaLearn AutoDL challenge 2019
Code submissions were executed on hidden tasks, with limited time and computational resources, pushing solutions that get results quickly.
Multi-Task Classification of Sewer Pipe Defects and Properties using a Cross-Task Graph Neural Network Decoder
In order to efficiently manage the sewerage infrastructure, automated sewer inspection has to be utilized.
Neural Implicit Surfaces for Efficient and Accurate Collisions in Physically Based Simulations
Nonetheless, their memory footprint also grows rapidly and their parallelization in a GPU is problematic due to their branching nature.
ChaLearn Looking at People: Inpainting and Denoising challenges
Dealing with incomplete information is a well studied problem in the context of machine learning and computational intelligence.
Deep unsupervised 3D human body reconstruction from a sparse set of landmarks
In this paper we propose the first deep unsupervised approach in human body reconstruction to estimate body surface from a sparse set of landmarks, so called DeepMurf.
PBNS: Physically Based Neural Simulator for Unsupervised Garment Pose Space Deformation
While deep-based approaches in the domain are becoming a trend, these are data-hungry models.
DeePSD: Automatic Deep Skinning And Pose Space Deformation For 3D Garment Animation
We present a novel solution to the garment animation problem through deep learning.
Computing the Testing Error without a Testing Set
Here, we derive an algorithm to estimate the performance gap between training and testing that does not require any testing dataset.
Cross-ethnicity Face Anti-spoofing Recognition Challenge: A Review
Although ethnic bias has been verified to severely affect the performance of face recognition systems, it still remains an open research problem in face anti-spoofing.
Multi-task human analysis in still images: 2D/3D pose, depth map, and multi-part segmentation
In this work, we analyze four related human analysis tasks in still images in a multi-task scenario by leveraging such datasets.
SMPLR: Deep SMPL reverse for 3D human pose and shape recovery
By implementing SMPLR as an encoder-decoder we avoid the need of complex constraints on pose and shape.
From 2D to 3D Geodesic-based Garment Matching
A new approach for 2D to 3D garment retexturing is proposed based on Gaussian mixture models and thin plate splines (TPS).
Deep Structure Inference Network for Facial Action Unit Recognition
In recent years, most efforts in automatic AU recognition have been dedicated to learning combinations of local features and to exploiting correlations between Action Units.
Explaining First Impressions: Modeling, Recognizing, and Explaining Apparent Personality from Videos
Explainability and interpretability are two critical aspects of decision support systems.
Depth-Based 3D Hand Pose Estimation: From Current Achievements to Future Goals
Official Torch7 implementation of "V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth Map", CVPR 2018
Ranked #5 on
Hand Pose Estimation
on HANDS 2017
End-to-end Global to Local CNN Learning for Hand Pose Recovery in Depth Data
Despite recent advances in 3D pose estimation of human hands, especially thanks to the advent of CNNs and depth cameras, this task is still far from being solved.
End-to-end semantic face segmentation with conditional random fields as convolutional, recurrent and adversarial networks
Recent years have seen a sharp increase in the number of related yet distinct advances in semantic segmentation.
