279 citations · 952 across the 35 of their papers we have counts for
6 papers · 1 filter
ELASTIC: Improving CNNs with Dynamic Scaling Policies
Huiyu Wang, Aniruddha Kembhavi, Ali Farhadi +2
Scale variation has been a challenge from traditional to modern approaches in computer vision. Most solutions to scale issues have a similar theme: a set of intuitive and manually…
Learning to Learn How to Learn: Self-Adaptive Visual Navigation Using Meta-Learning
Mitchell Wortsman, Kiana Ehsani, Mohammad Rastegari +2
Learning is an inherently continuous phenomenon. When humans learn a new task there is no explicit distinction between training and inference. As we learn a task, we keep learning…
ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural Network
Sachin Mehta, Mohammad Rastegari, Linda Shapiro +1
We introduce a light-weight, power efficient, and general purpose convolutional neural network, ESPNetv2, for modeling visual and sequential data. Our network uses group point-wise…
Pyramidal Recurrent Unit for Language Modeling
Sachin Mehta, Rik Koncel-Kedziorski, Mohammad Rastegari +1
LSTMs are powerful tools for modeling contextual information, as evidenced by their success at the task of language modeling. However, modeling contexts in very high dimensional sp…
Label Refinery: Improving ImageNet Classification through Label Progression
Hessam Bagherinezhad, Maxwell Horton, Mohammad Rastegari +1
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. However, studying labe…
ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation
Sachin Mehta, Mohammad Rastegari, Anat Caspi +2
We introduce a fast and efficient convolutional neural network, ESPNet, for semantic segmentation of high resolution images under resource constraints. ESPNet is based on a new con…