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Deep Learning Paper


Convolutional Neural Network Models

  • Rethinking the inception architecture for computer vision (2016), C. Szegedy et al. pdf
  • Inception-v4, inception-resnet and the impact of residual connections on learning (2016), C. Szegedy et al. pdf
  • Identity Mappings in Deep Residual Networks (2016), K. He et al. pdf
  • ResNet: Deep residual learning for image recognition (2016), K. He et al. pdf
  • Spatial transformer network (2015), M. Jaderberg et al., pdf
  • Going deeper with convolutions (2015), C. Szegedy et al. pdf
  • VGG: Very deep convolutional networks for large-scale image recognition (2014), K. Simonyan and A. Zisserman pdf
  • Return of the devil in the details: delving deep into convolutional nets (2014), K. Chatfield et al. pdf
  • OverFeat: Integrated recognition, localization and detection using convolutional networks (2013), P. Sermanet et al. pdf
  • Maxout networks (2013), I. Goodfellow et al. pdf
  • NIN: Network in network (2013), M. Lin et al. pdf
  • AlexNet: ImageNet classification with deep convolutional neural networks (2012), A. Krizhevsky et al. pdf

Image: Segmentation / Object Detection

  • YOLOv3: An Incremental Improvement(2018). pdf
  • YOLO9000: Better, Faster, Stronger(2016). pdf
  • YOLO: You only look once: Unified, real-time object detection (2016), J. Redmon et al. pdf
  • U-Net: Convolutional Networks for Biomedical Image Segmentation. pdf
  • SSD: Single Shot MultiBox Detector. pdf
  • FCN: Fully convolutional networks for semantic segmentation (2015), J. Long et al. pdf
  • Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks (2015), S. Ren et al. pdf
  • Fast R-CNN (2015), R. Girshick pdf
  • RCNN: Rich feature hierarchies for accurate object detection and semantic segmentation (2014), R. Girshick et al. pdf
  • Spatial pyramid pooling in deep convolutional networks for visual recognition (2014), K. He et al. pdf
  • DeepLabv4:Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation(2018). pdf
  • DeepLabv3:Rethinking Atrous Convolution for Semantic Image Segmentation(2017). pdf
  • DeepLabv2: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs(2016). pdf
  • DeepLabv1: Semantic image segmentation with deep convolutional nets and fully connected CRFs(2014). pdf

scene text detection/recognition paper

  • Deep Direct Regression for Multi-Oriented Scene Text Detection pdf
  • TextBoxes: A Fast Text Detector with a Single Deep Neural Network pdf
  • Detecting Text in Natural Image with Connectionist Text Proposal Network pdf
  • R2CNN: Rotational Region CNN for Orientation Robust Scene Text Detection pdf
  • EAST: An Efficient and Accurate Scene Text Detector pdf
  • Detecting Oriented Text in Natural Images by Linking Segments pdf
  • Arbitrary-Oriented Scene Text Detection via Rotation Proposals pdf
  • Scene Text Detection via Holistic, Multi-Channel Prediction pdf
  • Deep Matching Prior Network: Toward Tighter Multi-oriented Text Detection pdf

图题生成

  • Show and tell: A neural image caption generator, 2015 CVPRpdf
  • Show, attend and tell: Neural image caption generation with visual attention, 2015 ICMLpdf
  • VQA: Visual question answering (2015), S. Antol et al. pdf