Search Results for author:
Found 6 papers, 2 papers with code
Label Refinery: Improving ImageNet Classification through Label Progression
Among the three main components (data, labels, and models) of any supervised learning system, data and models have been the main subjects of active research.
Who Let The Dogs Out? Modeling Dog Behavior From Visual Data
We introduce the task of directly modeling a visually intelligent agent.
LCNN: Lookup-based Convolutional Neural Network
We introduce LCNN, a lookup-based convolutional neural network that encodes convolutions by few lookups to a dictionary that is trained to cover the space of weights in CNNs.
Newtonian Scene Understanding: Unfolding the Dynamics of Objects in Static Images
Direct and explicit estimation of the forces and the motion of objects from a single image is extremely challenging.
Are Elephants Bigger than Butterflies? Reasoning about Sizes of Objects
In this paper, we introduce a method to automatically infer object sizes, leveraging visual and textual information from web.
Newtonian Image Understanding: Unfolding the Dynamics of Objects in Static Images
Direct and explicit estimation of the forces and the motion of objects from a single image is extremely challenging.
