ZEPPELIN ドイツ腕時計ブランドの"ZEPPELIN"とのコラボレーションウォッチパートナ... 詳細を見る
![フェイスブック、コーディネートの悩みをAIで解明した論文「Fashion++」を発表](https://cdn-ak-scissors.b.st-hatena.com/image/square/fd2e76f7b6250035bc2b31602abe14ce1fb43cbe/height=288;version=1;width=512/https%3A%2F%2Ffashionsnap-assets.com%2Fasset%2Fformat%3Dauto%2Cwidth%3D1280%2Cheight%3D670%2Cgravity%3Dcenter%2Farticle%2Fimages%2F2019%2F11%2F191111-4-top.png)
ZEPPELIN ドイツ腕時計ブランドの"ZEPPELIN"とのコラボレーションウォッチパートナ... 詳細を見る
Powered by AI: Advancing product understanding and building new shopping experiences Today we’re announcing: We’ve built and deployed GrokNet, a universal computer vision system designed for shopping. It can identify fine-grained product attributes across billions of photos — in different categories, such as fashion, auto, and home decor. GrokNet is powering new Marketplace features for buyers and
Recognising detailed clothing characteristics (fine-grained attributes) in unconstrained images of people in-the-wild is a challenging task for computer vision, especially when there is only limited training data from the wild whilst most data available for model learning are captured in well-controlled environments using fashion models (well lit, no background clutter, frontal view, high-resoluti
curl -X PUT 'http://localhost:8080/services/ilsvrc_googlenet' -d '{ "description": "image classification service", "model": { "repository": "/opt/models/ilsvrc_googlenet", "init": "https://deepdetect.com/models/init/desktop/images/classification/ilsvrc_googlenet.tar.gz", "create_repository": true }, "mllib": "caffe", "type": "supervised", "parameters": { "input": { "connector": "image" } } }' curl
Clothing Co-Parsing by Joint Image Segmentation and Labeling Wei Yang1 , Ping Luo2 , Liang Lin1,3∗ 1 Sun Yat-sen University, Guangzhou, China 2 Department of Information Engineering, The Chinese University of Hong Kong 3 SYSU-CMU Shunde International Joint Research Institute, Shunde, China {platero.yang, pluo.lhi}@gmail.com, linliang@ieee.org Abstract This paper aims at developing an integrated sy
With the rapid proliferation of smart mobile devices, users now take millions of photos every day. These include large numbers of clothing and accessory images. We would like to answer questions like `What outfit goes well with this pair of shoes?' To answer these types of questions, one has to go beyond learning visual similarity and learn a visual notion of compatibility across categories. In th
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