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Classification

  • LeNet:Gradient-based learning applied to document recognition
  • NIN: Network In Network
  • AlexNet: ImageNet Classification with Deep Convolutional Neural Networks
  • VGG: Very Deep Convolutional Networks for Large-Scale Image Recognition
  • Inception
  • ResNet: Deep Residual Learning for Image Recognition
  • DenseNet: Densely Connected Convolutional Networks
  • Xception: Deep Learning with Depthwise Separable Convolutions
  • ResNeXt: Aggregated Residual Transformations for Deep Neural Networks
  • ResNeSt: Split-Attention Networks
  • BiT: Big Transfer

Basic

  • Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

Alpha Matting

  • MODNet: Trimap-Free Portrait Matting in Real Time
  • MODNet-V: Improving Portrait Video Matting via Background Restoration
  • RVM: Robust High-Resolution Video Matting with Temporal Guidance
  • UserClickMatting: Improved Image Matting via Real-time User Clicks and Uncertainty Estimation
  • BackgroundMattingv1: The World is Your Green Screen
  • BackgroundMattingv2:R eal-Time High-Resolution Background Matting
  • AlphaGAN: Generative adversarial networks for natural image matting
  • Attention-Guided Hierarchical Structure Aggregation for Image Matting
  • Deep Video Matting via Spatio-Temporal Alignment and Aggregation

Object Detection

  • Yolo: You Only Look Once: Unified, Real-Time Object Detection
  • Yolov2: Better, Faster
  • YOLOv3: An Incremental Improvement

Segmentation

  • Mask R-CNN
  • DeepLab
  • DFANet:Deep Feature Aggregation for Real-Time Semantic Segmentation
  • BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation
  • BiSeNet V2: Bilateral Network with Guided Aggregation for Real-time Semantic Segmentation

Style Transfer

  • A Neural Algorithm of Artistic Style
  • Perceptual Losses for Real-Time Style Transfer and Super-Resolution
  • Multi-style Generative Network for Real-time Transfer
  • Universal Style Transfer via Feature Transforms
  • Fast Patch-based Style Transfer of Arbitrary Style
  • Meta Networks for Neural Style Transfer
  • Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization
  • Learning Linear Transformations for Fast Image and Video Style Transfer
  • Coherent Online Video Style Transfer
  • ReCoNet: Real-time Coherent Video Style Transfer Network
  • Fast Video Multi-Style Transfer

GAN

  • GAN: Generative Adversarial Nets.
  • CycleGAN: Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
  • StyleGAN: A Style-Based Generator Architecture for Generative Adversarial Networks
  • Image2StyleGAN: How to Embed Images Into the StyleGAN Latent Space
  • Labels4Free: Unsupervised Segmentation using StyleGAN

FlowNet

  • FlowNet: Learning Optical Flow with Convolutional Networks
  • FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks

Re-ID

  • STA: Spatial-Temporal Attention for Large-Scale Video-based Person Re-Identification

SOD

  • Label Decoupling Framework for Salient Object Detection

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