* Rethinking Atrous Convolution for Semantic Image Segmentation (Google)
=> atrous convolution, DeepLabv3
* Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation (Google)
=> DeepLabv3+
* MentorNet, Regularizing Very Depp Neural Networks on Corrupted Lables
=> MentorNet
* Deep Neural Networks for YouTube Recommendations (Google)
* Attention-Based Models for Speech Recognition
* ASTER : An Attentional Scene Text Recognizer with Flexible Rectification (Baoguang Shi 등) - 2018
* FAN : Focusing Attention : Towards Accurate Text Recognition in Natural Images (Hikvision)
* CRAFT : Character Region Awareness for Text Detection (NAVER)
* What Is Wrong With Scene Text Recognition Model Comparisons? Dataset and Model Analysis
* Beyond a Gaussian Denoiser : Residual Learning of Deep CNN for Image Denoising
* Hybrid Task Cascade for Instnace Segmentation
* Improving Semantic Segmentation via Video Propagation and Label Relaxation
=> synthesizing new training samples
* Fixing the train-test resolution discrepancy (Facebook AI Research)
* Image Restoration Using Convolutional Auto-encoders with Symmetric Skip Connections
* DeepTrianle : A Deep Learning Approach to Loss Reserving (Kasa AI)
* U-GAT-IT : Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation (NCSOFT)
* On the Properties of Neural Machine Translation: Encoder-Decoder Approaches (Yoshua Bengio)
* Chinese Text in the Wild
* TedEval : A Fair Evaluation Metric for Scene Text Detectors (NAVER)
* RARE : Robust Scene Text Recognition with Automatic Rectification (Huazhong Uni, Baoguang Shi) - 2016
* Multi-Scale Attention with Dense Encoder for Handwritten Mathematical Expression Recognition (University of Science and Technology of China, Hefei, Anhui, P.R.China)
* Sequence-to-Sequence Domain Adaptation Network for Tobust Text Image Recognition - 2019
* An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition (Huazhong Uni, Baoguang Shi)
* Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition (Kaiming He)
* YOLACT++ : Better Real-time Instance Segmentaion
* Aggregation Cross-Entropy for Sequence Recognition
=> ACE loss function
* Large scale deep neural network acoustic modeling with semi-supervised training data for youtube video transcription (Google)
* FASTERSEG : Searching for faster real-time semantic segmentation (Horizon Robotics)
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