3.5k citations · 9.4k across the 54 of their papers we have counts for
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Quantification in-the-wild: data-sets and baselines
Oscar Beijbom, Judy Hoffman, Evan Yao +4
Quantification is the task of estimating the class-distribution of a data-set. While typically considered as a parameter estimation problem with strict assumptions on the data-set…
Adapting Deep Visuomotor Representations with Weak Pairwise Constraints
Eric Tzeng, Coline Devin, Judy Hoffman +5
Real-world robotics problems often occur in domains that differ significantly from the robot's prior training environment. For many robotic control tasks, real world experience is…
Spatial Semantic Regularisation for Large Scale Object Detection
Damian Mrowca, Marcus Rohrbach, Judy Hoffman +3
Large scale object detection with thousands of classes introduces the problem of many contradicting false positive detections, which have to be suppressed. Class-independent non-ma…
Simultaneous Deep Transfer Across Domains and Tasks
Eric Tzeng, Judy Hoffman, Trevor Darrell +1
Recent reports suggest that a generic supervised deep CNN model trained on a large-scale dataset reduces, but does not remove, dataset bias. Fine-tuning deep models in a new domain…
Cross Modal Distillation for Supervision Transfer
Saurabh Gupta, Judy Hoffman, Jitendra Malik
In this work we propose a technique that transfers supervision between images from different modalities. We use learned representations from a large labeled modality as a superviso…