27 citations · 48 across the 3 of their papers we have counts for
6 papers
Figure Captioning with Reasoning and Sequence-Level Training
Charles Chen, Ruiyi Zhang, Eunyee Koh +5
Figures, such as bar charts, pie charts, and line plots, are widely used to convey important information in a concise format. They are usually human-friendly but difficult for comp…
Deep GrabCut for Object Selection
Ning Xu, Brian Price, Scott Cohen +2
Most previous bounding-box-based segmentation methods assume the bounding box tightly covers the object of interest. However it is common that a rectangle input could be too large…
Automatic Annotation of Structured Facts in Images
Mohamed Elhoseiny, Scott Cohen, Walter Chang +2
Motivated by the application of fact-level image understanding, we present an automatic method for data collection of structured visual facts from images with captions. Example str…
Object Contour Detection with a Fully Convolutional Encoder-Decoder Network
Jimei Yang, Brian Price, Scott Cohen +2
We develop a deep learning algorithm for contour detection with a fully convolutional encoder-decoder network. Different from previous low-level edge detection, our algorithm focus…
Deep Interactive Object Selection
Ning Xu, Brian Price, Scott Cohen +2
Interactive object selection is a very important research problem and has many applications. Previous algorithms require substantial user interactions to estimate the foreground an…
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…