Papers with Code 2020 全年回顾
转载自:AI公园
作者:Ross Taylor
编译:ronghuaiyang
2020年Papers with Code 中最顶流的论文,代码和benchmark。
Papers with Code 中收集了各种机器学习的内容:论文,代码,结果,方便发现和比较。通过这些数据,我们可以了解ML社区中,今年哪些东西最有意思。下面我们总结了2020年最热门的带代码的论文、代码库和benchmark。
2020顶流论文
Tan等人的EfficientDet是2020年在Papers with Code上被访问最多的论文。
EfficientDet: Scalable and Efficient Object Detection — Tan et al https://paperswithcode.com/paper/efficientdet-scalable-and-efficient-object Fixing the train-test resolution discrepancy — Touvron et al https://paperswithcode.com/paper/fixing-the-train-test-resolution-discrepancy-2 ResNeSt: Split-Attention Networks — Zhang et al https://paperswithcode.com/paper/resnest-split-attention-networks Big Transfer (BiT) — Kolesnikov et al https://paperswithcode.com/paper/large-scale-learning-of-general-visual Object-Contextual Representations for Semantic Segmentation — Yuan et al https://paperswithcode.com/paper/object-contextual-representations-for Self-training with Noisy Student improves ImageNet classification — Xie et al https://paperswithcode.com/paper/self-training-with-noisy-student-improves YOLOv4: Optimal Speed and Accuracy of Object Detection — Bochkovskiy et al https://paperswithcode.com/paper/yolov4-optimal-speed-and-accuracy-of-object An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale — Dosovitskiy et al https://paperswithcode.com/paper/an-image-is-worth-16x16-words-transformers-1 Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer — Raffel et al https://paperswithcode.com/paper/exploring-the-limits-of-transfer-learning Hierarchical Multi-Scale Attention for Semantic Segmentation — Tao et al https://paperswithcode.com/paper/hierarchical-multi-scale-attention-for
2020顶流代码库
Transformers是2020年在Papers with Code上被访问最多的代码库
Transformers — Hugging Face — https://github.com/huggingface/transformers PyTorch Image Models — Ross Wightman — https://github.com/rwightman/pytorch-image-models Detectron2 — FAIR — https://github.com/facebookresearch/detectron2 InsightFace — DeepInsight — https://github.com/deepinsight/insightface Imgclsmob — osmr — https://github.com/osmr/imgclsmob DarkNet — pjreddie — https://github.com/pjreddie/darknet PyTorchGAN — Erik Linder-Norén — https://github.com/eriklindernoren/PyTorch-GAN MMDetection — OpenMMLab — https://github.com/open-mmlab/mmdetection FairSeq — PyTorch — https://github.com/pytorch/fairseq Gluon CV — DMLC — https://github.com/dmlc/gluon-cv
2020顶流Benchmarks
ImageNet是2020年在Papers with Code上访问最多的benchmark
ImageNet — Image Classification — https://paperswithcode.com/sota/image-classification-on-imagenet COCO — Object Detection / Instance Segmentation — https://paperswithcode.com/sota/object-detection-on-coco Cityscapes — Semantic Segmentation — https://paperswithcode.com/sota/semantic-segmentation-on-cityscapes CIFAR-10 — Image Classification — https://paperswithcode.com/sota/image-classification-on-cifar-10 CIFAR-100 — Image Classification — https://paperswithcode.com/sota/image-classification-on-cifar-100 PASCAL VOC 2012 — Semantic Segmentation — https://paperswithcode.com/sota/semantic-segmentation-on-pascal-voc-2012 MPII Human Pose — Pose Estimation — https://paperswithcode.com/sota/pose-estimation-on-mpii-human-pose Market-1501 — Person Re-Identification — https://paperswithcode.com/sota/person-re-identification-on-market-1501 MNIST — Image Classification — https://paperswithcode.com/sota/image-classification-on-mnist Human 3.6M — Human Pose Estimation -https://paperswithcode.com/sota/pose-estimation-on-mpii-human-pose
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