8 citations · 12 across the 3 of their papers we have counts for
3 papers · 1 filter
Low-Shot Validation: Active Importance Sampling for Estimating Classifier Performance on Rare Categories
Fait Poms, Vishnu Sarukkai, Ravi Teja Mullapudi +4
For machine learning models trained with limited labeled training data, validation stands to become the main bottleneck to reducing overall annotation costs. We propose a statistic…
Background Splitting: Finding Rare Classes in a Sea of Background
Ravi Teja Mullapudi, Fait Poms, William R. Mark +2
We focus on the real-world problem of training accurate deep models for image classification of a small number of rare categories. In these scenarios, almost all images belong to t…
Online Model Distillation for Efficient Video Inference
Ravi Teja Mullapudi, Steven Chen, Keyi Zhang +2
High-quality computer vision models typically address the problem of understanding the general distribution of real-world images. However, most cameras observe only a very small fr…