Make the Best of Face Clues in iQIYI Celebrity VideoIdentification Challenge 2019
Xi Fang, Ying Zou · 2019
iQIYI-VID-2019 is the largest video dataset for multi-modal person identification. It is composed of more than 200k video clips of 10,034 celebrities. Face is a critical clue for person identification when the face is visible in video. However face quality in a video may not always be good, and it also contains a lot of noise caused by detection and feature extraction. Meanwhile, conventional multi-modal person classification methods do not fully exploit the ability of face modality. They do not make full use of face detection confidence and quality evaluation indicators, which are key information in face modality. To address these issues, we develop a quality-based video face feature fusion method in inference with a quality-based face feature denoising and augmentation method in training. Our approach is only based on 512-dimensional face features provided by iQIYI-VID-2019 dataset. Utilizing our proposed novel method, we have achieved the mAP score of 89.83% which is the 4th place in iQIYI Celebrity Video Identification Challenge 2019.