Superpixel-guided Iterative Learning from Noisy Labels for Medical Image Segmentation

YOLOv3: An Incremental Improvement

Fast AutoAugment

YOLO9000: Better, Faster, Stronger

Efficient-CapsNet: Capsule Network with Self-Attention Routing

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

You Only Look Once: Unified, Real-Time Object Detection

SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization

Knowledge Distillation: A Survey

Going Deeper with Convolutions

Language Models are Few-Shot Learners

Attention Is All You Need

Railroad is not a Train: Saliency as Pseudo-pixel Supervision for Weakly Supervised Semantic Segmentation

Deep Residual Learning for Image Recognition

DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution

Rethinking the Heatmap Regression for Bottom-up Human Pose Estimation

Purifying Gaze Feature for Generalizable Gaze Estimation

Very Deep Convolutional Networks for Large-Scale Image Recognition

Meta Pseudo Labels

Visualizing and Understanding Convolutional Networks

An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

ImageNet Classification with Deep Convolutional Neural Networks

RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation

Deep Face Recognition: A Survey

Path Aggregation Network for Instance Segmentation

A Gift from Knowledge Distillation: Fast Optimization, Network Minimization and Transfer Learning

Transformer: Attention is all you need

PolyTransform: Deep Polygon Transformer for Instance Segmentation

SSD:Single Shot MultiBox Detector