2 code implementations • CVPR 2020 • Bo Chen, Golnaz Ghiasi, Hanxiao Liu, Tsung-Yi Lin, Dmitry Kalenichenko, Hartwig Adams, Quoc V. Le
We propose MnasFPN, a mobile-friendly search space for the detection head, and combine it with latency-aware architecture search to produce efficient object detection models.
Ranked #230 on Object Detection on COCO test-dev
2 code implementations • 25 Mar 2019 • Mason Liu, Menglong Zhu, Marie White, Yinxiao Li, Dmitry Kalenichenko
Models and examples built with TensorFlow
Ranked #31 on Video Object Detection on ImageNet VID (using extra training data)
22 code implementations • CVPR 2018 • Benoit Jacob, Skirmantas Kligys, Bo Chen, Menglong Zhu, Matthew Tang, Andrew Howard, Hartwig Adam, Dmitry Kalenichenko
The rising popularity of intelligent mobile devices and the daunting computational cost of deep learning-based models call for efficient and accurate on-device inference schemes.
155 code implementations • 17 Apr 2017 • Andrew G. Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, Hartwig Adam
We present a class of efficient models called MobileNets for mobile and embedded vision applications.
Ranked #238 on Object Detection on COCO test-dev
182 code implementations • CVPR 2015 • Florian Schroff, Dmitry Kalenichenko, James Philbin
On the widely used Labeled Faces in the Wild (LFW) dataset, our system achieves a new record accuracy of 99. 63%.
Ranked #1 on Disguised Face Verification on MegaFace