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Exploiting Egocentric Object Prior for 3D Saliency Detection
Gedas Bertasius, Hyun Soo Park, Jianbo Shi
On a minute-to-minute basis people undergo numerous fluid interactions with objects that barely register on a conscious level. Recent neuroscientific research demonstrates that hum…
Semantic Segmentation with Boundary Neural Fields
Gedas Bertasius, Jianbo Shi, Lorenzo Torresani
The state-of-the-art in semantic segmentation is currently represented by fully convolutional networks (FCNs). However, FCNs use large receptive fields and many pooling layers, bot…
Future Localization from an Egocentric Depth Image
Hyun Soo Park, Yedong Niu, Jianbo Shi
This paper presents a method for future localization: to predict a set of plausible trajectories of ego-motion given a depth image. We predict paths avoiding obstacles, between obj…
High-for-Low and Low-for-High: Efficient Boundary Detection from Deep Object Features and its Applications to High-Level Vision
Gedas Bertasius, Jianbo Shi, Lorenzo Torresani
Most of the current boundary detection systems rely exclusively on low-level features, such as color and texture. However, perception studies suggest that humans employ object-leve…