3.3k citations · 6.1k across the 51 of their papers we have counts for
3 papers · 1 filter
The Unreasonable Effectiveness of Noisy Data for Fine-Grained Recognition
Jonathan Krause, Benjamin Sapp, Andrew Howard +5
Current approaches for fine-grained recognition do the following: First, recruit experts to annotate a dataset of images, optionally also collecting more structured data in the for…
Generation and Comprehension of Unambiguous Object Descriptions
Junhua Mao, Jonathan Huang, Alexander Toshev +3
We propose a method that can generate an unambiguous description (known as a referring expression) of a specific object or region in an image, and which can also comprehend or inte…
Pose Embeddings: A Deep Architecture for Learning to Match Human Poses
Greg Mori, Caroline Pantofaru, Nisarg Kothari +4
We present a method for learning an embedding that places images of humans in similar poses nearby. This embedding can be used as a direct method of comparing images based on human…