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Found 11 papers, 1 papers with code
RipViz: Finding Rip Currents by Learning Pathline Behavior
To address this, we treat rip currents as a flow anomaly in an otherwise normal flow.
Tag-based annotation creates better avatars
Compared to direct annotation of labels, the proposed method: produces higher annotator agreements, causes machine learning to generates more consistent predictions, and only requires a marginal cost to add new rendering systems.
AgileAvatar: Stylized 3D Avatar Creation via Cascaded Domain Bridging
We propose a novel self-supervised learning framework to create high-quality stylized 3D avatars with a mix of continuous and discrete parameters.
How Much Does Input Data Type Impact Final Face Model Accuracy?
This idealized synthetic analysis is then compared to real results from several methods for constructing 3D faces from 2D photographs.
Automated Rip Current Detection with Region based Convolutional Neural Networks
This paper presents a machine learning approach for the automatic identification of rip currents with breaking waves.
DuelGAN: A Duel Between Two Discriminators Stabilizes the GAN Training
In this paper, we introduce DuelGAN, a generative adversarial network (GAN) solution to improve the stability of the generated samples and to mitigate mode collapse.
Ranked #3 on
Image Generation
on Fashion-MNIST
A Fine-grained Data Set and Analysis of Tangling in Bug Fixing Commits
Methods: We use a crowd sourcing approach for manual labeling to validate which changes contribute to bug fixes for each line in bug fixing commits.
Software Engineering
The AFRL-Ohio State WMT18 Multimodal System: Combining Visual with Traditional
AFRL-Ohio State extends its usage of visual domain-driven machine translation for use as a peer with traditional machine translation systems.
On Optimizing Human-Machine Task Assignments
When crowdsourcing systems are used in combination with machine inference systems in the real world, they benefit the most when the machine system is deeply integrated with the crowd workers.
Simultaneous Time-of-Flight Sensing and Photometric Stereo With a Single ToF Sensor
We present a novel system which incorporates photometric stereo with the Time-of-Flight depth sensor.
