👁 MMOCR: A Comprehensive Toolbox for Text Detection, Recognition and Understanding

MMOCR is an open-source toolbox based on PyTorch and mmdetection for text detection, text recognition

Github: https://github.com/open-mmlab/mmocr

Paper: https://arxiv.org/abs/2108.06543v1

Documentation: https://mmocr.readthedocs.io/en/latest/
👉 @bigdata_1

Guide To PyOD: A Python Toolkit For Outlier Detection

https://analyticsindiamag.com/guide-to-pyod-a-python-toolkit-for-outlier-detection/

👉 @bigdata_1

💡 X-modaler: A Versatile and High-performance Codebase for Cross-modal Analytics

Github: https://github.com/yehli/xmodaler

Paper: https://arxiv.org/abs/2108.08217v1

Project: https://xmodaler.readthedocs.io/en/latest/
👉 @bigdata_1

Hypercorrelation Squeeze for Few-Shot Segmentation

Github: https://github.com/juhongm999/hsnet

Paper: https://arxiv.org/abs/2104.01538v1

Project: http://cvlab.postech.ac.kr/research/HSNet/
👉 @bigdata_1

✔️ Fully Convolutional Networks for Panoptic Segmentation

Github: https://github.com/dvlab-research/panopticfcn

Paper: https://arxiv.org/pdf/2012.00720.pdf

Methods: https://paperswithcode.com/method/fcn
👉 @bigdata_1

Fourier Image Transformer

Github: https://github.com/juglab/FourierImageTransformer

Paper: https://arxiv.org/abs/2104.02555v1
👉 @bigdata_1

🔍 TOOD: Task-aligned One-stage Object Detection

Github: https://github.com/fcjian/TOOD

Paper: https://arxiv.org/abs/2108.07755v2

Dataset: https://paperswithcode.com/dataset/coco

SOLD² - Self-supervised Occlusion-aware Line Description and Detection

Github: https://github.com/cvg/SOLD2

Paper: https://arxiv.org/abs/2104.03362

🎩 Mr. TyDi: A Multi-lingual Benchmark for Dense Retrieval

Mr. TyDi is a multi-lingual benchmark dataset built on TyDi, covering eleven typologically diverse languages.

Github: https://github.com/castorini/mr.tydi

Paper: https://arxiv.org/abs/2108.08787

Tasks: https://paperswithcode.com/task/representation-learning
👉 @bigdata_1

MetricGAN: Generative Adversarial Networks based Black-box Metric Scores Optimization for Speech Enhancement

Github: https://github.com/speechbrain/speechbrain/tree/develop/recipes/Voicebank/enhance/MetricGAN

Paper: https://arxiv.org/abs/1905.04874
👉 @bigdata_1

🔗 A Unified Objective for Novel Class Discovery

Github: https://github.com/DonkeyShot21/UNO

Paper: https://arxiv.org/abs/2108.08536v2

Dataset: https://paperswithcode.com/dataset/cifar-100
👉 @bigdata_1

AutoGL: A Library for Automated Graph Learning

Github: https://github.com/THUMNLab/AutoGL

Paper: https://arxiv.org/abs/2104.04987v1
👉 @bigdata_1

🕸 Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark Study

Github: https://github.com/VITA-Group/Deep_GCN_Benchmarking

Paper: https://arxiv.org/abs/2108.10521v1
👉 @bigdata_1

Compact Transformers

Github: https://github.com/SHI-Labs/Compact-Transformers

Paper: https://arxiv.org/abs/2104.05704

👉 @bigdata_1

💡Volunteer computing: статья про коллаборативное обучение нейросети

Если вы хотите создавать большие модели, не имея суперкомпьютер за спиной, то вам понадобится технология, способная разделить вычисления между теми, кто готов предоставить вам мощности. В этом поможет технология DeDLOC, разработанная в Yandex Research, Hugging Face и University of Toronto.

Хабр: https://habr.com/ru/company/yandex/blog/574466/
👉 @bigdata_1

Shape and Material Capture at Home, CVPR 2021

Github: https://github.com/dlichy/ShapeAndMaterial

Paper: https://arxiv.org/abs/2104.06397v1
👉 @bigdata_1

How To Code RNN And LSTM Neural Networks In Python

https://www.nbshare.io/notebook/249468051/How-To-Code-RNN-and-LSTM-Neural-Networks-in-Python/
👉 @bigdata_1

🧍 Fast and Flexible Human Pose Estimation with HyperPose

Github: https://github.com/tensorlayer/hyperpose

Paper: https://arxiv.org/abs/2108.11826v1

Docs: https://hyperpose.readthedocs.io/en/latest/markdown/quick_start/prediction.html#table-of-flags-for-hyperpose-cli
👉 @bigdata_1

💬 Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation

Github: https://github.com/ofirpress/attention_with_linear_biases

Paper: https://ofir.io/train_short_test_long.pdf

Fairseq: https://github.com/pytorch/fairseq
👉 @bigdata_1

Generating Cats with StyleGAN on AWS SageMaker

https://devopstar.com/2019/02/25/generating-cats-with-stylegan-on-aws-sagemaker

Code: https://github.com/t04glovern/stylegan
👉 @bigdata_1

ShapeConv: Shape-aware Convolutional Layer for Indoor RGB-D Semantic Segmentation

Github: https://github.com/hanchaoleng/shapeconv

Paper: https://arxiv.org/abs/2108.10528v1
👉 @bigdata_1