166 citations · 180 across the 6 of their papers we have counts for
6 papers
Boosted Zero-Shot Learning with Semantic Correlation Regularization
Te Pi, Xi Li, Zhongfei +1
We study zero-shot learning (ZSL) as a transfer learning problem, and focus on the two key aspects of ZSL, model effectiveness and model adaptation. For effective modeling, we adop…
Graph-Theoretic Spatiotemporal Context Modeling for Video Saliency Detection
Lina Wei, Fangfang Wang, Xi Li +2
As an important and challenging problem in computer vision, video saliency detection is typically cast as a spatiotemporal context modeling problem over consecutive frames. As a re…
Group-wise Deep Co-saliency Detection
Lina Wei, Shanshan Zhao, Omar El Farouk Bourahla +2
In this paper, we propose an end-to-end group-wise deep co-saliency detection approach to address the co-salient object discovery problem based on the fully convolutional network (…
Deep Optical Flow Estimation Via Multi-Scale Correspondence Structure Learning
Shanshan Zhao, Xi Li, Omar El Farouk Bourahla
As an important and challenging problem in computer vision, learning based optical flow estimation aims to discover the intrinsic correspondence structure between two adjacent vide…
Deeply-Learned Part-Aligned Representations for Person Re-Identification
Liming Zhao, Xi Li, Jingdong Wang +1
In this paper, we address the problem of person re-identification, which refers to associating the persons captured from different cameras. We propose a simple yet effective human…
Transductive Zero-Shot Learning with a Self-training dictionary approach
Yunlong Yu, Zhong Ji, Xi Li +4
As an important and challenging problem in computer vision, zero-shot learning (ZSL) aims at automatically recognizing the instances from unseen object classes without training dat…