no code implementations • ECCV 2018 • Yancheng Bai, Yongqiang Zhang, Mingli Ding, Bernard Ghanem
In the MTGAN, the generator is a super-resolution network, which can up-sample small blurred images into fine-scale ones and recover detailed information for more accurate detection.
no code implementations • CVPR 2018 • Yongqiang Zhang, Yancheng Bai, Mingli Ding, Yongqiang Li, Bernard Ghanem
Finally, we use these pseudo ground-truths to train a fully-supervised detector.
no code implementations • CVPR 2018 • Yancheng Bai, Yongqiang Zhang, Mingli Ding, Bernard Ghanem
In this paper, we proposed an algorithm to directly generate a clear high-resolution face from a blurry small one by adopting a generative adversarial network (GAN).
no code implementations • 28 Jan 2018 • Yancheng Bai, Huijuan Xu, Kate Saenko, Bernard Ghanem
In this paper, we propose the contextual multi-scale region convolutional 3D network (CMS-RC3D) for activity detection.
no code implementations • 20 Jul 2017 • Yancheng Bai, Bernard Ghanem
We test our MB-FCN detector on two public face detection benchmarks, including FDDB and WIDER FACE.