20 citations · 45 across the 13 of their papers we have counts for
6 papers · 1 filter
SENSE: a Shared Encoder Network for Scene-flow Estimation
Huaizu Jiang, Deqing Sun, Varun Jampani +3
We introduce a compact network for holistic scene flow estimation, called SENSE, which shares common encoder features among four closely-related tasks: optical flow estimation, dis…
A New Confidence Interval for the Mean of a Bounded Random Variable
Erik Learned-Miller, Philip S. Thomas
We present a new method for constructing a confidence interval for the mean of a bounded random variable from samples of the random variable. We conjecture that the confidence inte…
Automatic adaptation of object detectors to new domains using self-training
Aruni RoyChowdhury, Prithvijit Chakrabarty, Ashish Singh +4
This work addresses the unsupervised adaptation of an existing object detector to a new target domain. We assume that a large number of unlabeled videos from this domain are readil…
Pixel-Adaptive Convolutional Neural Networks
Hang Su, Varun Jampani, Deqing Sun +3
Convolutions are the fundamental building block of CNNs. The fact that their weights are spatially shared is one of the main reasons for their widespread use, but it also is a majo…
Integrating Propositional and Relational Label Side Information for Hierarchical Zero-Shot Image Classification
Colin Samplawski, Heesung Kwon, Erik Learned-Miller +1
Zero-shot learning (ZSL) is one of the most extreme forms of learning from scarce labeled data. It enables predicting that images belong to classes for which no labeled training in…
Nonparametric Curve Alignment
Marwan Mattar, Michael Ross, Erik Learned-Miller
Congealing is a flexible nonparametric data-driven framework for the joint alignment of data. It has been successfully applied to the joint alignment of binary images of digits, bi…