Search Results for author: Andrew C. Gallagher

Found 5 papers, 1 papers with code

von Mises-Fisher Loss: An Exploration of Embedding Geometries for Supervised Learning

1 code implementation ICCV 2021 Tyler R. Scott, Andrew C. Gallagher, Michael C. Mozer

Recent work has argued that classification losses utilizing softmax cross-entropy are superior not only for fixed-set classification tasks, but also by outperforming losses developed specifically for open-set tasks including few-shot learning and retrieval.

Classification Few-Shot Learning +2

Modeling Uncertainty with Hedged Instance Embeddings

no code implementations ICLR 2019 Seong Joon Oh, Kevin P. Murphy, Jiyan Pan, Joseph Roth, Florian Schroff, Andrew C. Gallagher

Instance embeddings are an efficient and versatile image representation that facilitates applications like recognition, verification, retrieval, and clustering.

Metric Learning

A Mixed Bag of Emotions: Model, Predict, and Transfer Emotion Distributions

no code implementations CVPR 2015 Kuan-Chuan Peng, Tsuhan Chen, Amir Sadovnik, Andrew C. Gallagher

First, we show through psychovisual studies that different people have different emotional reactions to the same image, which is a strong and novel departure from previous work that only records and predicts a single dominant emotion for each image.

VIP: Finding Important People in Images

no code implementations CVPR 2015 Clint Solomon Mathialagan, Andrew C. Gallagher, Dhruv Batra

We address two specific questions -- Given an image, who are the most important individuals in it?

What's in a Name? First Names as Facial Attributes

no code implementations CVPR 2013 Huizhong Chen, Andrew C. Gallagher, Bernd Girod

We show that describing people in terms of similarity to a vector of possible first names is a powerful description of facial appearance that can be used for face naming and building facial attribute classifiers.

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