217 citations · 345 across the 12 of their papers we have counts for
4 papers · 1 filter
Low-Shot Learning with Imprinted Weights
Hang Qi, Matthew Brown, David G. Lowe
Human vision is able to immediately recognize novel visual categories after seeing just one or a few training examples. We describe how to add a similar capability to ConvNet class…
Deep Reinforcement Learning for Dexterous Manipulation with Concept Networks
Aditya Gudimella, Ross Story, Matineh Shaker +4
Deep reinforcement learning yields great results for a large array of problems, but models are generally retrained anew for each new problem to be solved. Prior learning and knowle…
Pose2Instance: Harnessing Keypoints for Person Instance Segmentation
Subarna Tripathi, Maxwell Collins, Matthew Brown +1
Human keypoints are a well-studied representation of people.We explore how to use keypoint models to improve instance-level person segmentation. The main idea is to harness the not…
Unsupervised Learning of Depth and Ego-Motion from Video
Tinghui Zhou, Matthew Brown, Noah Snavely +1
We present an unsupervised learning framework for the task of monocular depth and camera motion estimation from unstructured video sequences. We achieve this by simultaneously trai…