2 code implementations • 16 Apr 2024 • Danfeng Qin, Chas Leichner, Manolis Delakis, Marco Fornoni, Shixin Luo, Fan Yang, Weijun Wang, Colby Banbury, Chengxi Ye, Berkin Akin, Vaibhav Aggarwal, Tenghui Zhu, Daniele Moro, Andrew Howard
We present the latest generation of MobileNets, known as MobileNetV4 (MNv4), featuring universally efficient architecture designs for mobile devices.
no code implementations • ECCV 2020 • Yandong Li, Di Huang, Danfeng Qin, Liqiang Wang, Boqing Gong
They fail to improve object detectors in their vanilla forms due to the domain gap between the Web images and curated datasets.
1 code implementation • ICCV 2019 • Keren Ye, Mingda Zhang, Adriana Kovashka, Wei Li, Danfeng Qin, Jesse Berent
Learning to localize and name object instances is a fundamental problem in vision, but state-of-the-art approaches rely on expensive bounding box supervision.
no code implementations • 25 Nov 2018 • Keren Ye, Mingda Zhang, Wei Li, Danfeng Qin, Adriana Kovashka, Jesse Berent
To alleviate the cost of obtaining accurate bounding boxes for training today's state-of-the-art object detection models, recent weakly supervised detection work has proposed techniques to learn from image-level labels.
no code implementations • NeurIPS 2014 • Danfeng Qin, Xuanli Chen, Matthieu Guillaumin, Luc V. Gool
Matching local visual features is a crucial problem in computer vision and its accuracy greatly depends on the choice of similarity measure.
no code implementations • CVPR 2013 • Danfeng Qin, Christian Wengert, Luc van Gool
Furthermore, we propose a function to score the individual contributions into an image to image similarity within the probabilistic framework.