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Proud to attend the NVIDIA AI Lab cross-team meet-up held in CVPR 2017 and have received the brand-new TESLA V100 GPUs in person from NVIDIA CEO Jensen Huang.

利用CVPR 2017在夏威夷舉行,NVIDIA舉辦了跨國的NVIDIA AI Lab交流會。也很幸運成為第一批使用TESLA V100的實驗室。

Along with #CVPR2017, NVIDIA calls for the first cross-team meeting for the 18 NVIDIA AI Labs it supported in the past year. There are research teams from Berkeley, CAS, CMU, CUHK, DFKI, MIT, NTU, NYU, Oxford, Peking University, Stanford, Tsinghua, Univ of Washington, Università della Svizzera Italiana and SUPSI, Université de Montréal, University of Tokyo, University of Toronto, AI Institute Canada, etc.

It’s exciting to meet with and learn from so many outstanding research teams. It’s a further surprise for the appearance of NVIDIA CEO Jensen Huang.

One more surprise! Jensen announced the first batch of the brand new GPU, TESLA V100, are delivered to the 18 AI teams — before the official release date. Then each PI is called up for receiving the award, which also has his own signature and the best wish in “Do Great AI“!

Note that our team had received the awards from NVIDIA since November 2016 including a DGX-1 supercomputer and multi-year unrestricted research fund.

We are proud in one of the NVIDIA AI Labs and are proud to be in #CVPR2017 for presenting two prominent papers.

The V100 includes 640 Tensor Cores, delivering 120 teraflops of deep learning performance; Volta provides a 5x improvement in peak teraflops over its predecessor Pascal, and 15x over the Maxwell architecture, launched just two years ago.

 

Related news from NVIDIA corporate blog.
https://blogs.nvidia.com/blog/2017/07/22/tesla-v100-cvpr-nvail/

 

  Posts

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June 7th, 2018

First Place (#1) in Disguised Face Recognition in CVPR 2018

January 6th, 2019

意想不到的科技部「AI投資潛力獎第一名」

December 16th, 2018

Keep Recruiting for Machine Learning Research Partners for Numerous Visual Sensors

December 16th, 2018

FutureTech Demo and Breakthrough Award (未來科技突破獎)

October 12th, 2018

結合虛與實的試鞋生成網路 (Virtual Try-On Shoe with Generative Neural Networks)

我們都有這樣的困擾,在電子購物的時候,看到一雙好看的鞋子,想買。但是卻又拿不定主意自己穿起來好看嗎?或是搭配某件褲子適合嗎?怎麼讓網路虛擬商城的鞋子,可以有效試在自己的腳上呢? 這個工作的挑戰在於如何使用單張鞋子商品的照片,很自然的合成在使用者的腳上,而且腳可能會有各種姿勢、角度。如何客服這個問題? 很高興大學部專題生(EE) 周晁德 完成了這個 PIVTONS 的虛擬鞋子試穿生成網路,試著解決這個困擾大家很久的問題。 這個有趣的工作也將於十二月初,在澳洲珀斯舉辦 Asian Conference on Computer Vision (ACCV) 2018 以大會演說 (Oral) 的方式跟大家分享這個工作。接下來全新的測試資料集將會公開讓大家使用,如果可以的話,我們也將試試看將整個試穿生成系統上線,讓大家體驗虛擬試鞋的樂趣 — 可以多試穿,多省錢。 我們鼓勵high-risk的研究工作。令人慶幸的是,這工作的發想、資料收集都是專題生獨立完成。當然在過程當中遇到很多GAN生成的問題,網路設計、訓練的問題,幾乎放棄了,還好團隊成員一起想辦法解決,關關難過,關關過(甚至免費擔任model),讓這個兼具技術深度以及商業價值的系統,可以順利完成。 我們也一直努力,讓智能生成(或是辨識)系統,賦予更有意義的應用 […]

September 13th, 2018

Finalist (Top 3) in 2018 IEEE Signal Processing Society Video and Image Processing (VIP) Cup

July 29th, 2018

信手拈來的3D模型搜尋 (Cross-View and Cross-Domain 3D Model Search)

July 27th, 2018

低解析人臉辨識跟解析度放大 (Very Low-Resolution Face Hallucination and Recognition)

June 18th, 2018

Winning Third Place in CVPR 2018 Video Recognition Challenge — Moments in Time

June 13th, 2018

[Video Report] National Investment for the GPU Supercomputer?

June 9th, 2018

Amazing Crowd Size and Positive Feedbacks in the Deep Learning Lecture for GTC 2018 Taipei