Search Results for author: Shotaro Sano

Found 4 papers, 1 papers with code

Sampling Techniques for Large-Scale Object Detection from Sparsely Annotated Objects

no code implementations CVPR 2019 Yusuke Niitani, Takuya Akiba, Tommi Kerola, Toru Ogawa, Shotaro Sano, Shuji Suzuki

However, large datasets like Open Images Dataset v4 (OID) are sparsely annotated, and some measure must be taken in order to ensure the training of a reliable detector.

object-detection Object Detection

Optuna: A Next-generation Hyperparameter Optimization Framework

10 code implementations25 Jul 2019 Takuya Akiba, Shotaro Sano, Toshihiko Yanase, Takeru Ohta, Masanori Koyama

We will present the design-techniques that became necessary in the development of the software that meets the above criteria, and demonstrate the power of our new design through experimental results and real world applications.

Distributed Computing Hyperparameter Optimization

Team PFDet's Methods for Open Images Challenge 2019

no code implementations25 Oct 2019 Yusuke Niitani, Toru Ogawa, Shuji Suzuki, Takuya Akiba, Tommi Kerola, Kohei Ozaki, Shotaro Sano

Using this method, the team PFDet achieved 3rd and 4th place in the instance segmentation and the object detection track, respectively.

Instance Segmentation Object +4

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