Search Results for author: Phil Ammirato

Found 4 papers, 1 papers with code

A Mask-RCNN Baseline for Probabilistic Object Detection

no code implementations9 Aug 2019 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 dataset.

Object object-detection +1

Target Driven Instance Detection

1 code implementation13 Mar 2018 Phil Ammirato, Cheng-Yang Fu, Mykhailo Shvets, Jana Kosecka, Alexander C. Berg

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.

Object

A Dataset for Developing and Benchmarking Active Vision

no code implementations27 Feb 2017 Phil Ammirato, Patrick Poirson, Eunbyung Park, Jana Kosecka, Alexander C. Berg

We present a new public dataset with a focus on simulating robotic vision tasks in everyday indoor environments using real imagery.

Benchmarking General Classification +5

Fast Single Shot Detection and Pose Estimation

no code implementations19 Sep 2016 Patrick Poirson, Phil Ammirato, Cheng-Yang Fu, Wei Liu, Jana Kosecka, Alexander C. Berg

For applications in navigation and robotics, estimating the 3D pose of objects is as important as detection.

Object Tracking Pose Estimation

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