Deep Learning for Generic Object Detection: A Survey

paper : https://arxiv.org/abs/1809.02165v1
#computervision #deeplearning #patternrecognition @ArtificialIntelligenceArticles

Do Better ImageNet Models Transfer Better?

By Simon Kornblith, Jonathon Shlens, Quoc V. Le: https://arxiv.org/abs/1805.08974

#ComputerVision #PatternRecognition #MachineLearning

SlowFast Networks for Video Recognition

Feichtenhofer et al.: https://arxiv.org/abs/1812.03982

#MachineLearning #ComputerVision #DeepLearning #PatternRecognition #Technology

SC-FEGAN: Face Editing Generative Adversarial Network with User's Sketch and Color

Jo and Park: https://arxiv.org/abs/1902.06838f

GitHub: https://github.com/JoYoungjoo/SC-FEGAN

#ComputerVision #GenerativeAdversarialNetwork #PatternRecognition

Reversible Adversarial Examples
Liu et al.: https://arxiv.org/abs/1811.00189
#ComputerVision #PatternRecognition #MachineLearning #MontréalAI #NeuralNetworks

Machine learning and artificial intelligence in the quantum domain"
By Vedran Dunjko, Hans J. Briegel: https://arxiv.org/abs/1709.02779
#QuantumPhysics #ArtificialIntelligence #ComputerVision #MontrealAI #PatternRecognition

This one is a must read - the latest #ComputerVision #PatternRecognition https://deepai.org/publication/relational-action-forecasting

Meta-Sim: Learning to Generate Synthetic Datasets
Kar et al.: https://arxiv.org/abs/1904.11621 @ArtificialIntelligenceArticles
#ComputerVision #PatternRecognition #ArtificialIntelligence

Fast AutoAugment

Lim et al.:

https://arxiv.org/abs/1905.00397
Code:
https://github.com/KakaoBrain/fast-autoaugment

#MachineLearning #ComputerVision #PatternRecognition

Visualizing the Consequences of Climate Change Using Cycle-Consistent Adversarial Networks

Schmidt et al.: https://arxiv.org/abs/1905.03709

#ComputerVision #PatternRecognition #ArtificialIntelligence

Visualizing the Consequences of Climate Change Using Cycle-Consistent Adversarial Networks

Schmidt et al.: https://arxiv.org/abs/1905.03709

#ComputerVision #PatternRecognition #ArtificialIntelligence

Adaptive Neural Trees
Tanno et al.: https://arxiv.org/abs/1807.06699
#ArtificialIntelligence #ComputerVision #EvolutionaryComputing #MachineLearning #PatternRecognition

A key conference quality indicator is low paper acceptance rates. The CVPR 2019 paper acceptance rate dropped to 25.1 percent from last year’s 29.6 percent 🤓☝️

The list of all 1300 research papers accepted for CVPR 2019 is available here: https://openaccess.thecvf.com/CVPR2019.py

Given you spend 1 hour to read 1 article and the rate of 8 articles per day, it will take you about 6 months to read all of them. You'd better start right now 🙃

#CVPR2019 #computervision #patternrecognition #deeplearning #machinelearning

Complex-YOLO: Real-time 3D Object Detection on Point Clouds

Simon et al.: https://arxiv.org/abs/1803.06199

#ArtificialIntelligence #ComputerVision #DeepLearning #MachineLearning #PatternRecognition

Adaptive Neural Trees
Tanno et al.: https://arxiv.org/abs/1807.06699
#ArtificialIntelligence #ComputerVision #EvolutionaryComputing #MachineLearning #PatternRecognition