9 citations · 15 across the 4 of their papers we have counts for
6 papers
Balanced Filtering via Disclosure-Controlled Proxies
Siqi Deng, Emily Diana, Michael Kearns +1
We study the problem of collecting a cohort or set that is balanced with respect to sensitive groups when group membership is unavailable or prohibited from use at deployment time.…
Musketeer: Joint Training for Multi-task Vision Language Model with Task Explanation Prompts
Zhaoyang Zhang, Yantao Shen, Kunyu Shi +7
We present a vision-language model whose parameters are jointly trained on all tasks and fully shared among multiple heterogeneous tasks which may interfere with each other, result…
The Caltech Fish Counting Dataset: A Benchmark for Multiple-Object Tracking and Counting
Justin Kay, Peter Kulits, Suzanne Stathatos +5
We present the Caltech Fish Counting Dataset (CFC), a large-scale dataset for detecting, tracking, and counting fish in sonar videos. We identify sonar videos as a rich source of d…
Harnessing Unrecognizable Faces for Improving Face Recognition
Siqi Deng, Yuanjun Xiong, Meng Wang +2
The common implementation of face recognition systems as a cascade of a detection stage and a recognition or verification stage can cause problems beyond failures of the detector.…
Positive-Congruent Training: Towards Regression-Free Model Updates
Sijie Yan, Yuanjun Xiong, Kaustav Kundu +5
Reducing inconsistencies in the behavior of different versions of an AI system can be as important in practice as reducing its overall error. In image classification, sample-wise i…
SMOT: Single-Shot Multi Object Tracking
Wei Li, Yuanjun Xiong, Shuo Yang +2
We present single-shot multi-object tracker (SMOT), a new tracking framework that converts any single-shot detector (SSD) model into an online multiple object tracker, which emphas…