3.5k citations · 9.4k across the 54 of their papers we have counts for
3 papers · 1 filter
Deep Domain Confusion: Maximizing for Domain Invariance
Eric Tzeng, Judy Hoffman, Ning Zhang +2
Recent reports suggest that a generic supervised deep CNN model trained on a large-scale dataset reduces, but does not remove, dataset bias on a standard benchmark. Fine-tuning dee…
Detector Discovery in the Wild: Joint Multiple Instance and Representation Learning
Judy Hoffman, Deepak Pathak, Trevor Darrell +1
We develop methods for detector learning which exploit joint training over both weak and strong labels and which transfer learned perceptual representations from strongly-labeled a…
LSDA: Large Scale Detection Through Adaptation
Judy Hoffman, Sergio Guadarrama, Eric Tzeng +5
A major challenge in scaling object detection is the difficulty of obtaining labeled images for large numbers of categories. Recently, deep convolutional neural networks (CNNs) hav…