90 citations · 326 across the 21 of their papers we have counts for
6 papers · 1 filter
AiR: Attention with Reasoning Capability
Shi Chen, Ming Jiang, Jinhui Yang +1
While attention has been an increasingly popular component in deep neural networks to both interpret and boost performance of models, little work has examined how attention progres…
Saliency Prediction with External Knowledge
Yifeng Zhang, Ming Jiang, Qi Zhao
The last decades have seen great progress in saliency prediction, with the success of deep neural networks that are able to encode high-level semantics. Yet, while humans have the…
Leveraging Bottom-Up and Top-Down Attention for Few-Shot Object Detection
Xianyu Chen, Ming Jiang, Qi Zhao
Few-shot object detection aims at detecting objects with few annotated examples, which remains a challenging research problem yet to be explored. Recent studies have shown the effe…
-Reference Transfer Learning for Saliency Prediction
Yan Luo, Yongkang Wong, Mohan S. Kankanhalli +1
Benefiting from deep learning research and large-scale datasets, saliency prediction has achieved significant success in the past decade. However, it still remains challenging to p…
GradMix: Multi-source Transfer across Domains and Tasks
Junnan Li, Ziwei Xu, Yongkang Wong +2
The computer vision community is witnessing an unprecedented rate of new tasks being proposed and addressed, thanks to the deep convolutional networks' capability to find complex m…
Direction Concentration Learning: Enhancing Congruency in Machine Learning
Yan Luo, Yongkang Wong, Mohan S. Kankanhalli +1
One of the well-known challenges in computer vision tasks is the visual diversity of images, which could result in an agreement or disagreement between the learned knowledge and th…