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Found 6 papers, 2 papers with code
Rethinking Reprojection: Closing the Loop for Pose-Aware Shape Reconstruction From a Single Image
An emerging problem in computer vision is the reconstruction of 3D shape and pose of an object from a single image.
Rethinking Reprojection: Closing the Loop for Pose-aware ShapeReconstruction from a Single Image
An emerging problem in computer vision is the reconstruction of 3D shape and pose of an object from a single image.
Deep-LK for Efficient Adaptive Object Tracking
In this paper we present a new approach for efficient regression based object tracking which we refer to as Deep- LK.
Need for Speed: A Benchmark for Higher Frame Rate Object Tracking
In this paper, we propose the first higher frame rate video dataset (called Need for Speed - NfS) and benchmark for visual object tracking.
Learning Background-Aware Correlation Filters for Visual Tracking
Correlation Filters (CFs) have recently demonstrated excellent performance in terms of rapidly tracking objects under challenging photometric and geometric variations.
Correlation Filters with Limited Boundaries
In this paper, we propose a novel approach to correlation filter estimation that: (i) takes advantage of inherent computational redundancies in the frequency domain, and (ii) dramatically reduces boundary effects.
