Real-Time Monocular Segmentation and Pose Tracking of Multiple Objects | https://www.youtube.com/watch?v=-nFkNPqf1LU
YouTube
Real-Time Monocular Segmentation and Pose Tracking of Multiple Objects (ECCV'16)
The video shows a real-time system capable of segmenting multiple 3D objects and tracking their pose using a single RGB camera, based on prior shape knowledge. The system uses twist-coordinates for pose parametrization and a pixel-wise second-order optimization…
A MNIST-like fashion product database by Zalando | #deeplearning #dataset
https://github.com/zalandoresearch/fashion-mnist
https://github.com/zalandoresearch/fashion-mnist
GitHub
GitHub - zalandoresearch/fashion-mnist: A MNIST-like fashion product database. Benchmark
A MNIST-like fashion product database. Benchmark :point_down: - GitHub - zalandoresearch/fashion-mnist: A MNIST-like fashion product database. Benchmark
Apple: "We developed the facial matching neural
networks using over a BILLION images, including IR and depth images collected in studies conducted with the participants’ informed consent".
https://images.apple.com/business/docs/FaceID_Security_Guide.pdf
networks using over a BILLION images, including IR and depth images collected in studies conducted with the participants’ informed consent".
https://images.apple.com/business/docs/FaceID_Security_Guide.pdf
Apple Support
Apple Platform Security
Learn how security is implemented in Apple hardware, software, apps, and services.
DeepLab_v3: The best semantic image segmentation via neural network | #deeplearning #sourcecode #argovision
DeepLab_v3 (paper): https://arxiv.org/pdf/1706.05587.pdf
DeepLab_v2 (code): https://bitbucket.org/aquariusjay/deeplab-public-ver2/overview
DeepLab_v3 (paper): https://arxiv.org/pdf/1706.05587.pdf
DeepLab_v2 (code): https://bitbucket.org/aquariusjay/deeplab-public-ver2/overview
Noise suppression library with recurrent neural networks | #deeplearning #sourcecode #argovision
https://github.com/xiph/rnnoise/
https://github.com/xiph/rnnoise/
GitHub
GitHub - xiph/rnnoise: Recurrent neural network for audio noise reduction
Recurrent neural network for audio noise reduction - xiph/rnnoise
Evolution of previous "Neural Architecture Search w/ Reinf. Learning": Neural Optimizer Search w/ Reinf. Learning | #deeplearning #sourcecode
https://github.com/nutszebra/neural_architecture_search_with_reinforcement_learning_appendix_a
https://github.com/nutszebra/neural_architecture_search_with_reinforcement_learning_appendix_a
GitHub
GitHub - nutszebra/neural_architecture_search_with_reinforcement_learning_appendix_a: Implementation of Appendix A (Neural Architecture…
Implementation of Appendix A (Neural Architecture Search with Reinforcement Learning: https://arxiv.org/abs/1611.01578) by chainer - GitHub - nutszebra/neural_architecture_search_with_reinforcement...
Million-Scale Face Recognition: the biggest dataset ever for face recognition | #dataset #argovision
http://megaface.cs.washington.edu/
http://megaface.cs.washington.edu/
The @NVidia #NVDLA project promotes a standardized, open source, open architecture for #DeepLearning to rule the market | #sourcecode #argovision
https://github.com/nvdla/
https://github.com/nvdla/
GitHub
nvdla
NVDLA Open Source Project. nvdla has 17 repositories available. Follow their code on GitHub.
I'm very excited to announce ARGO Vision has been selected by #Nvidia to join the Inception Program!
#argovision #AIInception #startup
#argovision #AIInception #startup
GANs are broken at both the computational and algorithmic levels | #DeepLearning #computervision #argovision
Paper: https://arxiv.org/abs/1705.10461
Paper: https://arxiv.org/abs/1705.10461
arXiv.org
The Numerics of GANs
In this paper, we analyze the numerics of common algorithms for training Generative Adversarial Networks (GANs). Using the formalism of smooth two-player games we analyze the associated gradient...
A “standard intelligence model” to try unifying artificial & human intelligence | #deeplearning #argovision #AI
https://arxiv.org/ftp/arxiv/papers/1709/1709.10242.pdf
https://arxiv.org/ftp/arxiv/papers/1709/1709.10242.pdf
3D Real-Time #AugmentedReality hair. Dataset labeling: 6 years long | #deeplearning #AI #NeuralNetworks #argovision
https://youtu.be/KrswN0jFCwY
https://youtu.be/KrswN0jFCwY
YouTube
ModiFace 3D Real-Time Video Hair Coloration Demo
Generative 3D Shapes Using Autoencoder Networks | #deeplearning #computervision #NeuralNetworks
https://www.youtube.com/watch?time_continue=2&v=25xQs0Hs1z0
https://www.youtube.com/watch?time_continue=2&v=25xQs0Hs1z0
YouTube
Exploring Generative 3D Shapes Using Autoencoder Networks
We propose a new algorithm for converting unstructured triangle meshes into ones with a consistent topology for machine learning applications. We combine the...
Turning a horse into a zebra by CycleGAN | #deeplearning #sourcecode #argovision
https://www.youtube.com/watch?time_continue=1&v=9reHvktowLY
https://www.youtube.com/watch?time_continue=1&v=9reHvktowLY
YouTube
Turning a horse video into a zebra video (by CycleGAN)
GitHub: https://github.com/junyanz/CycleGAN Project: https://junyanz.github.io/CycleGAN/ Unpaired Image-to-Image Translation using Cycle-Consistent Adversari...
AVA: A Finely Labeled Video Dataset for Human Action Understanding | https://research.googleblog.com/2017/10/announcing-ava-finely-labeled-video.html
Research Blog
Announcing AVA: A Finely Labeled Video Dataset for Human Action Understanding
Posted by Chunhui Gu & David Ross, Software Engineers Teaching machines to understand human actions in videos is a fundamental research pr...
One pixel attack for fooling deep neural networks | https://arxiv.org/pdf/1710.08864.pdf
Latent space interpolation on Cifar by #Nvidia research | #deeplearning #argovision #artificialintelligence #NeuralNetworks #computervision