Papers with Code 2020 : A Year in Review

Ross Taylor
Dec 30, 2020 · 3 min read

Papers with Code indexes various machine learning artifacts — papers, code, results — to facilitate discovery and comparison. Using this data we can get a sense of what the ML community found useful and interesting this year. Below we summarize the top trending papers, libraries and benchmarks for 2020 on Papers with Code.

Top Trending Papers of 2020

EfficientDet by Tan et al was the most viewed paper on Papers with Code for 2020
  1. EfficientDet: Scalable and Efficient Object Detection — Tan et al
  2. Fixing the train-test resolution discrepancy — Touvron et al
  3. ResNeSt: Split-Attention Networks — Zhang et al
  4. Big Transfer (BiT) — Kolesnikov et al
  5. Object-Contextual Representations for Semantic Segmentation — Yuan et al
  6. Self-training with Noisy Student improves ImageNet classification — Xie et al
  7. YOLOv4: Optimal Speed and Accuracy of Object Detection — Bochkovskiy et al
  8. An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale — Dosovitskiy et al
  9. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer — Raffel et al
  10. Hierarchical Multi-Scale Attention for Semantic Segmentation — Tao et al

Top Trending Libraries of 2020

🤗 Transformers was the most viewed library on Papers with Code for 2020
  1. Transformers — Hugging Face —
  2. PyTorch Image Models — Ross Wightman —
  3. Detectron2 — FAIR —
  4. InsightFace — DeepInsight —
  5. Imgclsmob — osmr —
  6. DarkNet — pjreddie —
  7. PyTorchGAN — Erik Linder-Norén —
  8. MMDetection — OpenMMLab —
  9. FairSeq — PyTorch —
  10. Gluon CV — DMLC —

Top Trending Benchmarks of 2020

ImageNet was the most viewed benchmark on Papers with Code for 2020
  1. ImageNet — Image Classification —
  2. COCO — Object Detection / Instance Segmentation —
  3. Cityscapes — Semantic Segmentation —
  4. CIFAR-10 — Image Classification —
  5. CIFAR-100 — Image Classification —
  6. PASCAL VOC 2012 — Semantic Segmentation —
  7. MPII Human Pose — Pose Estimation —
  8. Market-1501 — Person Re-Identification —
  9. MNIST — Image Classification —
  10. Human 3.6M — Human Pose Estimation -

Congratulations to all the authors and developers for making an impact in the ML community this year!

Don’t forget to subscribe to our newsletter if you want to receive biweekly summaries of trending papers with code, libraries, community reimplementations and benchmarks.

Thanks to Elvis Saravia for helping put this piece together


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