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Human vision greatly benefits from the information about sizes of objects. The role of size in several visual reasoning tasks has been thoroughly explored in human perception and cognition. However, the impact of the information about sizes of objects is yet to be determined in AI. We postulate that this is mainly attributed to the lack of a comprehensive… (More)

- Roozbeh Mottaghi, Hessam Bagherinezhad, Mohammad Rastegari, Ali Farhadi
- 2016 IEEE Conference on Computer Vision and…
- 2016

In this paper, we study the challenging problem of predicting the dynamics of objects in static images. Given a query object in an image, our goal is to provide a physical understanding of the object in terms of the forces acting upon it and its long term motion as response to those forces. Direct and explicit estimation of the forces and the motion of… (More)

- Hessam Bagherinezhad, Mohammad Rastegari, Ali Farhadi
- 2017 IEEE Conference on Computer Vision and…
- 2017

Porting state of the art deep learning algorithms to resource constrained compute platforms (e.g. VR, AR, wearables) is extremely challenging. We propose a fast, compact, and accurate model for convolutional neural networks that enables efficient learning and inference. We introduce LCNN, a lookup-based convolutional neural network that encodes convolutions… (More)

- Pariya Raoufi, Habib Rostami, Hessam Bagherinezhad
- Inf. Sci.
- 2013

A linear arrangement / of an undirected graph G = (V,E) with jVj = n nodes is a bijective function /:V ? {0, . . . , n 1}. The cost function is costðG;/Þ 1⁄4 P uv2Ejð/ðuÞ /ðvÞÞj and opt(G) = min"/cost(G,/). The problem of finding opt(G) is called minimum linear arrangement (MINLA). The Minimum Linear Arrangement is an NP-hard problem in general. But there… (More)

High dimensional vectors appear frequently in recent development in CS, examples of which are user-movie ratings of netflix, DNA strings of patients, and images pixel values. In this lecture we study higher dimensions geometry and see how randomization help us to design algorithm. We first start with a few definitions, then we discuss several properties of… (More)

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