[1906.09756] Cascade R-CNN: High Quality Object Detection and Instance Segmentation

In object detection, the intersection over union (IoU) threshold is frequently used to define positives/negatives. The threshold used to train a detector defines its \textit{quality}. While the commonly used threshold of 0.5 leads to noisy (low-quality) detections, detection performance frequently degrades for larger thresholds. This paradox of high-quality detection has two causes: 1) overfitting, due to vanishing positive samples for large thresholds, and 2) inference-time quality mismatch between detector and test hypotheses. A multi-stage object detection architecture, the Cascade R-CNN, composed of a sequence of detectors trained with increasing IoU thresholds, is proposed to address these problems. The detectors are trained sequentially, using the output of a detector as training set for the next. This resampling progressively improves hypotheses quality, guaranteeing a positive training set of equivalent size for all detectors and minimizing overfitting. The same cascade is appl

1 mentions: @Maxwell_110
Date:

Referring Tweets

@Maxwell_110
@Maxwell_110 Cascade R-CNN 📝 t.co/07cmqY7RWy 推論される bbox の擬陽性数低減のため,学習の進行に伴って,徐々に IoU 閾値(学習用の正例判定用)を大きくしていく 閾値別に mask/class head があり,Boosting-like に bbox の品質を改善していく Detectron2 実装 ➡︎ t.co/gkOiPrtwA0 t.co/7GY2EiAKfZ

Related Entries

Prostate cANcer graDe Assessment (PANDA) Challenge | Kaggle
Read more Prostate cANcer graDe Assessment (PANDA) Challenge | Kaggle
0 users, 1 mentions 2020/07/22 17:21
Bottleneck Transformers for Visual Recognition | Papers With Code
Read more Bottleneck Transformers for Visual Recognition | Papers With Code
0 users, 1 mentions 2021/02/11 11:21
AIcrowd | Getting Started | Posts
Read more AIcrowd | Getting Started | Posts
0 users, 1 mentions 2021/07/31 04:38
232 - Semantic Segmentation of BraTS2020 - Part 1 - Getting the data ready - YouTube
Read more 232 - Semantic Segmentation of BraTS2020 - Part 1 - Getting the data ready - YouTube
0 users, 1 mentions 2021/09/04 00:09
[1908.10063] FinBERT: Financial Sentiment Analysis with Pre-trained Language Models
Read more [1908.10063] FinBERT: Financial Sentiment Analysis with Pre-trained Language Models
0 users, 1 mentions 2021/10/05 22:37
Tidy Data and Geoms for Bayesian Models • tidybayes
Read more Tidy Data and Geoms for Bayesian Models • tidybayes
0 users, 1 mentions 2021/10/23 10:37

ML-Newsについて

ML-Newsは機械学習に関するニュースサイトです。機械学習に関する論文、ブログ、ライブラリ、コンペティション、発表資料、勉強会などの最新の情報にアクセスできます。

機械学習を応用した自然言語処理、画像認識、情報検索などの分野の情報や機械学習で必要になるデータ基盤やMLOpsの話題もカバーしています。
安定したサイト運営のためにGitHub sponsorを募集しています。

お知らせ

  • 2021/12/31: デザインを刷新しました
  • 2021/04/08: 日本語とKaggleのカテゴリを新設しました