1640500214_maxresdefault.jpg
11.60K
04:57

Two Minute Papers: NVIDIA’s New AI: Journey Into Virtual Reality!

❤️ Train a neural network and track your experiments with Weights & Biases here: http://wandb.me/paperintro 📝 The paper “Physics-based Human Motion Estimation and Synthesis from Videos” is available here: https://nv-tlabs.github.io/physics-pose-estimation-project-page/ 🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Aleksandr Mashrabov, Alex Balfanz, Alex Haro, Andrew Melnychuk, Angelos […]
1640478557_maxresdefault.jpg
13.20K
05:32

Two Minute Papers: Enhance! Super Resolution Is Here! 🔍

❤️ Check out Lambda here and sign up for their GPU Cloud: https://lambdalabs.com/papers 📝 The paper “Image Super-Resolution via Iterative Refinement ” is available here: https://iterative-refinement.github.io/ https://github.com/Janspiry/Image-Super-Resolution-via-Iterative-Refinement 🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Aleksandr Mashrabov, Alex Haro, Andrew Melnychuk, Angelos Evripiotis, Benji Rabhan, Bryan Learn, […]
1640456924_maxresdefault.jpg
256
04:12

Two Minute Papers: Visually Indicated Sounds | Two Minute Papers #79

The Scholarly Store is available here: https://shop.spreadshirt.net/TwoMinutePapers Using the power of deep learning, it is now possible to create a technique that looks at a silent video and synthesize appropriate sound effects for it. The usage is at the moment, limited to hitting these objects with a drumstick. Note: The authors seem to lean on […]
1640435280_maxresdefault.jpg
277
05:35

Two Minute Papers: What Can We Learn From Deep Learning Programs? | Two Minute Papers #75

The paper “Model Compression” is available here: https://www.cs.cornell.edu/~caruana/compression.kdd06.pdf There is also a talk on it here: http://research.microsoft.com/apps/video/default.aspx?id=103668&r=1 Discussions on this issue: 1. https://www.linkedin.com/pulse/computer-vision-research-my-deep-depression-nikos-paragios 2. https://www.reddit.com/r/MachineLearning/comments/4lq701/yann_lecuns_letter_to_cvpr_chair_after_bad/ Recommended for you: Neural Programmer Interpreters – https://www.youtube.com/watch?v=B70tT4WMyJk WE WOULD LIKE TO THANK OUR GENEROUS PATREON SUPPORTERS WHO MAKE TWO MINUTE PAPERS POSSIBLE: David Jaenisch, Sunil Kim, Julian Josephs. https://www.patreon.com/TwoMinutePapers […]
1640413571_maxresdefault.jpg
242
04:48

Two Minute Papers: Estimating Matrix Rank With Neural Networks | Two Minute Papers #94

This tongue in cheek work is about identifying matrix ranks from images, plugging in a convolutional neural network where it is absolutely inaproppriate to use. The paper “Visually Identifying Rank” is available here: http://www.oneweirdkerneltrick.com/rank.pdf David Fouhey’s website is available here: http://www.cs.cmu.edu/~dfouhey/ The machine learning calculator is available here: http://armlessjohn404.github.io/calcuMLator/ The paper “Separable Subsurface Scattering” is […]
1640391879_maxresdefault.jpg
240
03:34

Two Minute Papers: Deep Learning and Cancer Research | Two Minute Papers #64

A few quite exciting applications of deep learning in cancer research have appeared recently. This new algorithm can recognize cancer cells by looking at blood samples without introducing any intrusive chemicals in the process. Amazing results ahead. 🙂 _________________________ The paper “Deep Learning in Label-free Cell Classification” is available here: http://www.nature.com/articles/srep21471 The link from Healthline: […]
1640370184_hqdefault.jpg
285
03:29

Two Minute Papers: Training Deep Neural Networks With Dropout | Two Minute Papers #62

In this episode, we discuss the bane of many machine learning algorithms – overfitting. It is also explained why it is an undesirable way to learn and how to combat it via dropout. _____________________ The paper “Dropout: A Simple Way to Prevent Neural Networks from Overtting” is available here: https://www.cs.toronto.edu/~hinton/absps/JMLRdropout.pdf Andrej Karpathy’s autoencoder is available […]
1640348415_maxresdefault.jpg
304
04:34

Two Minute Papers: Overfitting and Regularization For Deep Learning | Two Minute Papers #56

In this episode, we discuss the bane of many machine learning algorithms – overfitting. It is also explained why it is an undesirable way to learn and how to combat it via L1 and L2 regularization. _____________________________ The paper “Regression Shrinkage and Selection via the Lasso” is available here: http://statweb.stanford.edu/~tibs/lasso/lasso.pdf Andrej Karpathy’s excellent lecture notes […]
1640305111_maxresdefault.jpg
406
03:18

Two Minute Papers: Shape2vec: Understanding 3D Shapes With AI | Two Minute Papers #138

The paper “Shape2Vec: semantic-based descriptors for 3D shapes, sketches and images” is available here: http://www.cl.cam.ac.uk/research/rainbow/projects/shape2vec/ Code (coming soon according to the authors): https://github.com/ftasse/Shape2Vec WE WOULD LIKE TO THANK OUR GENEROUS PATREON SUPPORTERS WHO MAKE TWO MINUTE PAPERS POSSIBLE: Andrew Melnychuk, Claudio Fernandes, Daniel John Benton, Dave Rushton-Smith, Sunil Kim, VR Wizard. https://www.patreon.com/TwoMinutePapers Subscribe if you […]
1640261781_maxresdefault.jpg
609
02:45

Two Minute Papers: Digital Creatures Learn to Navigate in 3D | Two Minute Papers #153

The paper “DeepLoco: Dynamic Locomotion Skills Using Hierarchical Deep Reinforcement Learning” is available here: http://www.cs.ubc.ca/~van/papers/2017-TOG-deepLoco/index.html Two Minute Papers Merch: US: http://twominutepapers.com/ EU/Worldwide: https://shop.spreadshirt.net/TwoMinutePapers/ WE WOULD LIKE TO THANK OUR GENEROUS PATREON SUPPORTERS WHO MAKE TWO MINUTE PAPERS POSSIBLE: Andrew Melnychuk, Christian Lawson, Dave Rushton-Smith, Dennis Abts, e, Esa Turkulainen, Michael Albrecht, Sunil Kim, VR Wizard. […]
1640240061_maxresdefault.jpg
468
03:18

Two Minute Papers: Semantic Scene Completion From One Depth Image | Two Minute Papers #147

The paper “Semantic Scene Completion from a Single Depth Image” is available here: http://sscnet.cs.princeton.edu/ Recommended for you: How Does Deep Learning Work? – https://www.youtube.com/watch?v=He4t7Zekob0 Artificial Neural Networks and Deep Learning – https://www.youtube.com/watch?v=rCWTOOgVXyE WE WOULD LIKE TO THANK OUR GENEROUS PATREON SUPPORTERS WHO MAKE TWO MINUTE PAPERS POSSIBLE: Andrew Melnychuk, Christian Lawson, Daniel John Benton, Dave […]
1640225340_maxresdefault.jpg
11
10:01

KORNIA AI: LOW LEVEL COMPUTER VISION FOR AI

Kornia is a differentiable library that allows classical computer vision to be integrated into deep learning models. It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation […]
1640218318_maxresdefault.jpg
557
03:08

Two Minute Papers: AI Learns Geometric Descriptors From Depth Images | Two Minute Papers #148

The paper “3DMatch: Learning Local Geometric Descriptors from RGB-D Reconstructions” is available here: http://3dmatch.cs.princeton.edu/ Recommended for you: Our earlier episode on Siamese networks – https://www.youtube.com/watch?v=a3sgFQjEfp4 WE WOULD LIKE TO THANK OUR GENEROUS PATREON SUPPORTERS WHO MAKE TWO MINUTE PAPERS POSSIBLE: Andrew Melnychuk, Christian Lawson, Daniel John Benton, Dave Rushton-Smith, Esa Turkulainen, Sunil Kim, VR Wizard. […]
1640196579_maxresdefault.jpg
289
05:31

Two Minute Papers: What is Optimization? + Learning Gradient Descent | Two Minute Papers #82

Let’s talk about what mathematical optimization is, how gradient descent can solve simpler optimization problems, and Google DeepMind’s proposed algorithm that automatically learn optimization algorithms. The paper “Learning to learn by gradient descent by gradient descent” is available here: http://arxiv.org/pdf/1606.04474v1.pdf Source code: https://github.com/deepmind/learning-to-learn ______________________________ Recommended for you: Gradients, Poisson’s Equation and Light Transport – https://www.youtube.com/watch?v=sSnDTPjfBYU […]
1640174926_maxresdefault.jpg
451
03:05

Two Minute Papers: Automatic Hair Modeling from One Image | Two Minute Papers #92

This time, we are going to talk about hair modeling – obtaining hair geometry information from a photograph. This geometry information we can use in our movies and computer games. We can also run simulations on them and see how they look on a digital character. This is a remarkably difficult problem and you’ll see […]
1640153251_maxresdefault.jpg
552
02:57

Two Minute Papers: Learning to Fill Holes in Images | Two Minute Papers #130

The paper “Scene Completion Using Millions of Photographs” is available here: http://graphics.cs.cmu.edu/projects/scene-completion/scene-completion.pdf WE WOULD LIKE TO THANK OUR GENEROUS PATREON SUPPORTERS WHO MAKE TWO MINUTE PAPERS POSSIBLE: Claudio Fernandes, Daniel John Benton, Dave Rushton-Smith, Sunil Kim. https://www.patreon.com/TwoMinutePapers Subscribe if you would like to see more of these! – http://www.youtube.com/subscription_center?add_user=keeroyz Music: Dat Groove by Audionautix is […]
1640066588_maxresdefault.jpg
573
03:04

Two Minute Papers: Stable Neural Style Transfer | Two Minute Papers #136

The paper “Stable and Controllable Neural Texture Synthesis and Style Transfer Using Histogram Losses” is available here: https://arxiv.org/abs/1701.08893 Texture synthesis survey: http://www-sop.inria.fr/reves/Basilic/2009/WLKT09/ WE WOULD LIKE TO THANK OUR GENEROUS PATREON SUPPORTERS WHO MAKE TWO MINUTE PAPERS POSSIBLE: Andrew Melnychuk, Claudio Fernandes, Daniel John Benton, Dave Rushton-Smith, Sunil Kim, VR Wizard. https://www.patreon.com/TwoMinutePapers Subscribe if you would […]
1640044927_maxresdefault.jpg
412
03:05

Two Minute Papers: Photorealistic Images from Drawings | Two Minute Papers #80

The Two Minute Papers subreddit is available here: https://www.reddit.com/r/twominutepapers/ By using a convolutional neural networks (a powerful deep learning technique), it is now possible to build an application that takes a rough sketch as an input, and fetches photorealistic images from a database. ___________________________________ The paper “The Sketchy Database: Learning to Retrieve Badly Drawn Bunnies” […]