70 citations · 150 across the 5 of their papers we have counts for
5 papers
Rethinking Reprojection: Closing the Loop for Pose-aware ShapeReconstruction from a Single Image
Rui Zhu, Hamed Kiani Galoogahi, Chaoyang Wang +1
An emerging problem in computer vision is the reconstruction of 3D shape and pose of an object from a single image. Hitherto, the problem has been addressed through the application…
Deep-LK for Efficient Adaptive Object Tracking
Chaoyang Wang, Hamed Kiani Galoogahi, Chen-Hsuan Lin +1
In this paper we present a new approach for efficient regression based object tracking which we refer to as Deep- LK. Our approach is closely related to the Generic Object Tracking…
Need for Speed: A Benchmark for Higher Frame Rate Object Tracking
Hamed Kiani Galoogahi, Ashton Fagg, Chen Huang +2
In this paper, we propose the first higher frame rate video dataset (called Need for Speed - NfS) and benchmark for visual object tracking. The dataset consists of 100 videos (380K…
Learning Background-Aware Correlation Filters for Visual Tracking
Hamed Kiani Galoogahi, Ashton Fagg, Simon Lucey
Correlation Filters (CFs) have recently demonstrated excellent performance in terms of rapidly tracking objects under challenging photometric and geometric variations. The strength…
Correlation Filters with Limited Boundaries
Hamed Kiani Galoogahi, Terence Sim, Simon Lucey
Correlation filters take advantage of specific properties in the Fourier domain allowing them to be estimated efficiently: O(NDlogD) in the frequency domain, versus O(D^3 + ND^2) s…