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5 papers · 2 filters
iGOS++: Integrated Gradient Optimized Saliency by Bilateral Perturbations
Saeed Khorram, Tyler Lawson, Fuxin Li
The black-box nature of the deep networks makes the explanation for "why" they make certain predictions extremely challenging. Saliency maps are one of the most widely-used local e…
Where Are You? Localization from Embodied Dialog
Meera Hahn, Jacob Krantz, Dhruv Batra +4
We present Where Are You? (WAY), a dataset of ~6k dialogs in which two humans -- an Observer and a Locator -- complete a cooperative localization task. The Observer is spawned at r…
One Explanation is Not Enough: Structured Attention Graphs for Image Classification
Vivswan Shitole, Li Fuxin, Minsuk Kahng +2
Attention maps are a popular way of explaining the decisions of convolutional networks for image classification. Typically, for each image of interest, a single attention map is pr…
Semantic MapNet: Building Allocentric Semantic Maps and Representations from Egocentric Views
Vincent Cartillier, Zhile Ren, Neha Jain +3
We study the task of semantic mapping - specifically, an embodied agent (a robot or an egocentric AI assistant) is given a tour of a new environment and asked to build an allocentr…
Deep Variational Instance Segmentation
Jialin Yuan, Chao Chen, Li Fuxin
Instance Segmentation, which seeks to obtain both class and instance labels for each pixel in the input image, is a challenging task in computer vision. State-of-the-art algorithms…