Jinwon Lee

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PR-366: A ConvNet for 2020s

PR-355: Masked Autoencoders Are Scalable Vision Learners

PR-344: A Battle of Network Structures: An Empirical Study of CNN, Transformer, and MLP

PR-330: How To Train Your ViT? Data, Augmentation, and Regularization in Vision Transformers

PR-317: MLP-Mixer: An all-MLP Architecture for Vision

PR-297: Training data-efficient image transformers & distillation through attention

PR-284: End-to-End Object Detection with Transformers(DETR)

PR-270: PP-YOLO: An Effective and Efficient Implementation of Object Detector

PR-258: From ImageNet to Image Classification: Contextualizing Progress on Benchmarks

PR243: Designing Network Design Spaces

PR-231: A Simple Framework for Contrastive Learning of Visual Representations

PR-217: EfficientDet: Scalable and Efficient Object Detection

PR-207: YOLOv3: An Incremental Improvement

PR-197: One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers

PR-183: MixNet: Mixed Depthwise Convolutional Kernels