Welcome Prof. Rongrong Ji, ​from School of Informatics, Xiamen University, China to be Keynote Speaker!


Prof. Rongrong Ji, IEEE Senior Member, “Minjiang”Chair Professor, Fujian Province, School of Informatics, 

Xiamen University, China (click)

Research Area: Computer Vision, Multimedia and Machine Learning

Associate or Guest Editors in the following journals:

· ACM Transactions on Intelligent Systems and Technology

· IEEE Multimedia Magazine

· Signal Processing

· Neurocomputing

· Multimedia Tools and Applications

· ACM Multimedia Systems

· Frontiers of Computer Science

· Visual Communication and Image Representation

· The Visual Computer

Title: Semi-Supervised Adversarial Monocular Depth Estimation

Abstract: In this research, we address the problem of monocular depth estimation when only a limited number of training image-depth pairs are available. To achieve a high regression accuracy, the state-of-the-art estimation methods rely on CNNs trained with a large number of image-depth pairs, which are prohibitively costly or even infeasible to acquire. Aiming to break the curse of such expensive data collections, we propose a semi-supervised adversarial learning framework that only utilizes a small number of image-depth pairs in conjunction with a large number of easily-available monocular images to achieve high performance. In particular, we use one generator to regress the depth and two discriminators to evaluate the predicted depth, i.e., one inspects the image-depth pair while the other inspects the depth channel alone. These two discriminators provide their feedbacks to the generator as the loss to generate more realistic and accurate depth predictions. Experiments show that the proposed approach can improve most state-of-the-art models on the NYUD v2 dataset by effectively.