Search Results for author: Aaron Adcock

Found 8 papers, 6 papers with code

The Ring of Algebraic Functions on Persistence Bar Codes

2 code implementations2 Apr 2013 Aaron Adcock, Erik Carlsson, Gunnar Carlsson

We study the ring of algebraic functions on the space of persistence barcodes, with applications to pattern recognition.

Rings and Algebras 13Pxx, 68T10

Forward Prediction for Physical Reasoning

1 code implementation18 Jun 2020 Rohit Girdhar, Laura Gustafson, Aaron Adcock, Laurens van der Maaten

Physical reasoning requires forward prediction: the ability to forecast what will happen next given some initial world state.

Visual Reasoning

PyTorchVideo: A Deep Learning Library for Video Understanding

1 code implementation18 Nov 2021 Haoqi Fan, Tullie Murrell, Heng Wang, Kalyan Vasudev Alwala, Yanghao Li, Yilei Li, Bo Xiong, Nikhila Ravi, Meng Li, Haichuan Yang, Jitendra Malik, Ross Girshick, Matt Feiszli, Aaron Adcock, Wan-Yen Lo, Christoph Feichtenhofer

We introduce PyTorchVideo, an open-source deep-learning library that provides a rich set of modular, efficient, and reproducible components for a variety of video understanding tasks, including classification, detection, self-supervised learning, and low-level processing.

Self-Supervised Learning Video Understanding

A Systematic Study of Bias Amplification

1 code implementation27 Jan 2022 Melissa Hall, Laurens van der Maaten, Laura Gustafson, Maxwell Jones, Aaron Adcock

To enable this study, we design a simple image-classification problem in which we can tightly control (synthetic) biases.

BIG-bench Machine Learning Image Classification

Vision-Language Models Performing Zero-Shot Tasks Exhibit Gender-based Disparities

no code implementations26 Jan 2023 Melissa Hall, Laura Gustafson, Aaron Adcock, Ishan Misra, Candace Ross

With these capabilities in mind, we ask: Do vision-language models exhibit gender bias when performing zero-shot image classification, object detection and semantic segmentation?

Image Classification object-detection +4

FACET: Fairness in Computer Vision Evaluation Benchmark

no code implementations ICCV 2023 Laura Gustafson, Chloe Rolland, Nikhila Ravi, Quentin Duval, Aaron Adcock, Cheng-Yang Fu, Melissa Hall, Candace Ross

We present a new benchmark named FACET (FAirness in Computer Vision EvaluaTion), a large, publicly available evaluation set of 32k images for some of the most common vision tasks - image classification, object detection and segmentation.

Fairness Image Classification +3

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