16 citations · 33 across the 3 of their papers we have counts for
4 papers
A Mask-RCNN Baseline for Probabilistic Object Detection
Phil Ammirato, Alexander C. Berg
The Probabilistic Object Detection Challenge evaluates object detection methods using a new evaluation measure, Probability-based Detection Quality (PDQ), on a new synthetic image…
Target Driven Instance Detection
Phil Ammirato, Cheng-Yang Fu, Mykhailo Shvets +2
While state-of-the-art general object detectors are getting better and better, there are not many systems specifically designed to take advantage of the instance detection problem.…
A Dataset for Developing and Benchmarking Active Vision
Phil Ammirato, Patrick Poirson, Eunbyung Park +2
We present a new public dataset with a focus on simulating robotic vision tasks in everyday indoor environments using real imagery. The dataset includes 20,000+ RGB-D images and 50…
Fast Single Shot Detection and Pose Estimation
Patrick Poirson, Phil Ammirato, Cheng-Yang Fu +3
For applications in navigation and robotics, estimating the 3D pose of objects is as important as detection. Many approaches to pose estimation rely on detecting or tracking parts…