Search Results for author:
Found 7 papers, 5 papers with code
Editable Indoor Lighting Estimation
We present a method for estimating lighting from a single perspective image of an indoor scene.
RGB-D-E: Event Camera Calibration for Fast 6-DOF Object Tracking
In this paper, we propose, for the first time, to use an event-based camera to increase the speed of 3D object tracking in 6 degrees of freedom.
Input Dropout for Spatially Aligned Modalities
Computer vision datasets containing multiple modalities such as color, depth, and thermal properties are now commonly accessible and useful for solving a wide array of challenging tasks.
Deep Template-based Object Instance Detection
In this context, we propose a generic 2D object instance detection approach that uses example viewpoints of the target object at test time to retrieve its 2D location in RGB images, without requiring any additional training (i. e. fine-tuning) step.
Fast Spatially-Varying Indoor Lighting Estimation
We propose a real-time method to estimate spatiallyvarying indoor lighting from a single RGB image.
A Framework for Evaluating 6-DOF Object Trackers
We present a challenging and realistic novel dataset for evaluating 6-DOF object tracking algorithms.
Deep 6-DOF Tracking
We present a temporal 6-DOF tracking method which leverages deep learning to achieve state-of-the-art performance on challenging datasets of real world capture.
