output
20152020
most citedBag of Freebies for Training Object Detection Neural Networks

147 citations

Showing 2017Show all

5 papers · 1 filter

cs.RO20175 cited

Semantic Segmentation from Limited Training Data

A. Milan, T. Pham, K. Vijay +22

We present our approach for robotic perception in cluttered scenes that led to winning the recent Amazon Robotics Challenge (ARC) 2017. Next to small objects with shiny and transpa…

cs.LG201724 cited

A Generic Approach for Escaping Saddle points

Sashank J Reddi, Manzil Zaheer, Suvrit Sra +4

A central challenge to using first-order methods for optimizing nonconvex problems is the presence of saddle points. First-order methods often get stuck at saddle points, greatly d…

cs.CV20179 cited

Joint Learning of Set Cardinality and State Distribution

S. Hamid Rezatofighi, Anton Milan, Qinfeng Shi +2

We present a novel approach for learning to predict sets using deep learning. In recent years, deep neural networks have shown remarkable results in computer vision, natural langua…

cs.DS20171 cited

A High-Performance Algorithm for Identifying Frequent Items in Data Streams

Daniel Anderson, Pryce Bevan, Kevin Lang +3

Estimating frequencies of items over data streams is a common building block in streaming data measurement and analysis. Misra and Gries introduced their seminal algorithm for the…

cs.CV20172 cited

3D Face Morphable Models "In-the-Wild"

James Booth, Epameinondas Antonakos, Stylianos Ploumpis +3

3D Morphable Models (3DMMs) are powerful statistical models of 3D facial shape and texture, and among the state-of-the-art methods for reconstructing facial shape from single image…