👶🏻 👩🏼‍🚀 👩🏿‍🏭 शीर्षक "आपके लिए लेख पढ़ें।" मार्च 2020. भाग 2 🍿 ✈️ 👋

नमस्कार, हेब्र!

हम चैनल #article_essense से ओपन डेटा साइंस समुदाय के सदस्यों के वैज्ञानिक लेखों की समीक्षाओं को प्रकाशित करना जारी रखते हैं। यदि आप उन्हें हर किसी से पहले प्राप्त करना चाहते हैं - समुदाय में शामिल हों ! मार्च समीक्षा विधानसभा का पहला भाग पहले प्रकाशित किया गया था ।

1. NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis

: Ben Mildenhall, Pratul P. Srinivasan, Matthew Tancik, Jonathan T. Barron, Ravi Ramamoorthi, Ren Ng (UC Berkeley, Google Research, UC San Diego, 2020)
:: GitHub project :: Video :: Blog
: ( belskikh)

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2. Scene Text Recognition via Transformer

: Xinjie Feng, Hongxun Yao, Yuankai Qi, Jun Zhang, Shengping Zhang (China, 2020)
:: GitHub project
: ( belskikh)

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3. PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization

: (Imperial College London, Google Research, 2019)

: ( yorko)

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4. Lagrangian Neural Networks

: Miles Cranmer, Sam Greydanus, Stephan Hoyer, Peter Battaglia, David Spergel, Shirley Ho (Princeton, Oregon, Google, Flatiron, 2020)
:: GitHub project :: Blog
: ( graviton)

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5. Deformable Style Transfer

: Sunnie S. Y. Kim, Nicholas Kolkin, Jason Salavon, Gregory Shakhnarovich (Chicago, USA, 2020)

: ( digitman)

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L_{s t y l e} (I_{s}, X) + L_{s t y l e} (I_{s}, W (X, θ)) .

$L_{style}(I_s,X) + L_{style}(I_s,W(X,\theta)).$

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L_{w a r p} (P, P^{'}, θ) = \frac{1}{k} \sum_{i = 1}^{k} | | (p_{i} + θ_{i}) - p_{i}^{'} | |_{2}

$L_{warp}(P,P',\theta)=\frac{1}{k}\sum^k_{i=1}||(p_i + \theta_i) - p'_i||_2$

— deformation loss k , p_i p_i' — source target . θ. , p_i' p_i, , , - source target . "total variation norm of the 2D warp field". .

R_{T V} (f) = \frac{1}{W H} \sum_{i = 1}^{W} \sum_{j = 1}^{H} | | f_{i + 1, j} - f_{i, j} | |_{1} + | | f_{i, j + 1} - f_{i, j} | |_{1}

$R_{TV}(f)=\frac{1}{W H}\sum^W_{i=1}\sum^H_{j=1}||f_{i+1, j} - f_{i,j}||_1 + ||f_{i, j+1} - f_{i,j}||_1$

L (X, θ, I_{c}, I_{s}, P) = α L_{c o n t e n t} (I_{c}, X) + L_{s t y l e} (I_{s}, X) + L_{s t y l e} (I_{s}, W (X, θ)) + β L_{w a r p} (P, P^{'}, θ) + γ R_{T V} (f_{t h e t a}),

$L(X, \theta, I_c, I_s, P) = \alpha L_{content}(I_c, X) + L_{style}(I_s,X) + L_{style}(I_s,W(X,\theta)) \\+ \beta L_{warp}(P, P', \theta) + \gamma R_{TV}(f_{theta}),$

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6. Rethinking Few-Shot Image Classification: a Good Embedding Is All You Need?

: Yonglong Tian, Yue Wang, Dilip Krishnan, Joshua B. Tenenbaum, Phillip Isola (MIT, Google, 2020)
:: GitHub project
: ( belskikh)

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7. Attentive CutMix: An Enhanced Data Augmentation Approach for Deep Learning Based Image Classification

: Devesh Walawalkar, Zhiqiang Shen, Zechun Liu, Marios Savvides (Carnegie Mellon University, USA, 2020)

: ( artgor)

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CIFAR-10 — 80 , batch size 32, learning rate 1e-3, weight decay 1e-5;
CIFAR-100 — 120 , batch size 32, learning rate 1e-3, weight decay 1e-5;
ImageNet — 100 ResNet DenseNet, 180 EfficientNet, batch size 64, learning rate 1e-3

Ablation study

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शीर्षक "आपके लिए लेख पढ़ें।" मार्च 2020. भाग 2