205 citations · 572 across the 30 of their papers we have counts for
4 papers · 1 filter
Sherlock: Scalable Fact Learning in Images
Mohamed Elhoseiny, Scott Cohen, Walter Chang +2
We study scalable and uniform understanding of facts in images. Existing visual recognition systems are typically modeled differently for each fact type such as objects, actions, a…
LCNN: Low-level Feature Embedded CNN for Salient Object Detection
Hongyang Li, Huchuan Lu, Zhe Lin +2
In this paper, we propose a novel deep neural network framework embedded with low-level features (LCNN) for salient object detection in complex images. We utilise the advantage of…
Inner and Inter Label Propagation: Salient Object Detection in the Wild
Hongyang Li, Huchuan Lu, Zhe Lin +2
In this paper, we propose a novel label propagation based method for saliency detection. A key observation is that saliency in an image can be estimated by propagating the labels e…
Joint Object and Part Segmentation using Deep Learned Potentials
Peng Wang, Xiaohui Shen, Zhe Lin +3
Segmenting semantic objects from images and parsing them into their respective semantic parts are fundamental steps towards detailed object understanding in computer vision. In thi…