CVPR 2017: Conference Report

Tommi Kerola

2017-08-17 10:00:50

Writers: Richard Calland, Tommi Kerola

Preferred Networks (PFN) attended the CVPR 2017 conference in Honolulu, U.S., one of the flagship conferences for discussing research and applications in computer vision and pattern recognition. Computer vision is of major importance for our activities at PFN, including applications for autonomous driving, robotics, and of course products such as PaintsChainer. Modern computer vision is largely based on deep learning, which is relevant for our continued research and product development. In this blog post, we will briefly summarize trends from this conference, focusing on a few papers relevant to each topic.

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ChainerCV Release

Yusuke Niitani

2017-08-14 11:07:10

We released ChainerCV: a utility library for computer vision in deep learning. This library aims at making the process of training and applying deep learning models for computer vision easier using Chainer. It contains high quality implementations of computer vision models, and tools that are necessary to conduct research in this field.

GitHub page: https://github.com/chainer/chainercv
Documentation: http://chainercv.readthedocs.io/en/stable/

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IETF 99 Report

Hirochika Asai

2017-08-08 14:01:13

Hello! I’m Hirochika Asai, working as a researcher at Preferred Networks (PFN). I joined PFN from this April. Today, I briefly report the 99th meeting of the Internet Engineering Task Force (IETF) (IETF 99) in this post. I participated in IETF 99, held at Hilton Prague, Prague, Czech. It was the first attendance to the IETF meetings from PFN.

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Publish 2017 PFN Internship Coding Tasks

Kosuke Nakago

2017-08-01 11:23:51

* Japanese blog is also written here.

Preferred Networks (PFN) organizes two-month-long summer internship program for students in August and September every year.

The number of applications is increasing year by year. This year we have received the highest number of applications ever and the interview and selection process has been finished.

PFN 2017 Summer Internship Program

 

Then we have published our intern coding tasks on github.

https://github.com/pfnet/intern-coding-tasks

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FCN-Based 6D Robotic Grasping for Arbitrary Placed Objects

kusano

2017-07-25 10:01:28

Hello! My name is Hitoshi Kusano. I participated in 2016 PFN summer internship program and have been a part-time engineer at PFN ever since, while also studying machine learning at Kyoto University. At PFN, my research topic was to teach an industrial robot how to pick up an object.

Based on the result of my work at PFN, I presented a paper titled ”FCN-Based 6D Robotic Grasping for Arbitrary Placed Objects” at the Learning and Control for Autonomous Manipulation Systems: The Role of Dimensionality Reduction workshop at ICRA 2017, the world’s biggest annual conference in robotics.

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Pieter Abbeel becomes Technical Advisor at Preferred Networks

hido

2017-07-24 12:00:56

Today, Preferred Networks is pleased to announce that Professor Pieter Abbeel, UC Berkeley and OpenAI, will be appointed as a technical advisor. PFN researchers and engineers are very excited about this news and looking forward to working with him.

Prof. Pieter Abbeel

 

Though he does not require any introduction, let me share the story behind it in the following.

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ICLR 2017: Conference Report & Coming ICML

miyato

2017-07-21 11:20:57

I am Takeru Miyato, a researcher at Preferred Networks (PFN), and I participated in  ICLR 2017 (4/24-4/26), which is the biggest conference on deep learning research.

Let me give you a brief overview of the event. ICLR has been held since 2013 and this was the fifth ICLR. The main features of ICLR are:

  • Focus on deep learning and its application. Most of the papers focus on neural networks.
  • Adaptation of open review system. Everyone can join the review process. To be precise, everyone can see the all of the reviews and rebuttals and also can comment, ask questions, and post his or her reviews as public reviews. In addition, authors can update their paper anytime from the feedback until the end of the discussion phase.

As far as I know, there is no other conference exposing the all of the reviews and rebuttals to the public, which I think is interesting / helpful to the people who write or review research papers. Also, some people analyzed the submissions and reviews, and they posted articles with interesting results. Here are some links to a pair of interesting ones:

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IV 2017: Conference Report

maruyama

2017-07-13 10:56:42

Writers: Tommi Kerola, Shintarou Okada, Shirou Maruyama

Preferred Networks (PFN) was present at the IEEE IV 2017 conference in Redondo Beach, CA, US, one of the flagship conferences for discussing research and applications for intelligent vehicles, including techniques for autonomous driving. Autonomous driving is one of the fields of main importance for PFN, which is why three of our members attended the conference in order to learn more about the latest research, and to connect with people from both academia and the industry. In this blog post, we will briefly summarize trends from this conference, focusing mainly on perception and motion planning.

 

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Chainer-GAN-lib Release

matsumoto

2017-07-11 10:30:40

We released chainer-GAN-lib: the collection of Chainer implementation of recent GAN variants. This library is targeted to those who think “the progress of GAN is too fast and hard to follow”, “Experiments in GAN articles can not be reproduced at all”, “How can I implement the gradient penalty with Chainer?”

https://github.com/pfnet-research/chainer-gan-lib

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Preferred Networks during ICRA: Conference Report

jethrotan

2017-07-03 11:30:12

Preferred Networks (PFN) was present at IEEE ICRA 2017, world’s biggest annual robotics conference, as exhibitor, invited speaker, and silver grade sponsor. A total of 3221 people attended the conference this year, which is more than double of last year’s attendance. As robotics is one of the fields of major importance within PFN, we have sent as much as ten of our members to attend ICRA.

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