13,683 research outputs found
The Fractured Memory of a Mind’s Eye
The work I create is informed by questioning reality/identity, the fractalizing planes
of existence our essence occupies, and the artifacts of memory experience navigating
through space time. While existing in this realm of oversaturated media and neon
glow, I question the effects of pervasive data systems overloading or programming the
mental software we possess. My work includes humor as a means of exploring these
conventions while also displaying psychedelic surrealist imagery to help break away
from the conscious prison this existence births our concept apparatuses within
Footprints and Free Space from a Single Color Image
Understanding the shape of a scene from a single color image is a formidable
computer vision task. However, most methods aim to predict the geometry of
surfaces that are visible to the camera, which is of limited use when planning
paths for robots or augmented reality agents. Such agents can only move when
grounded on a traversable surface, which we define as the set of classes which
humans can also walk over, such as grass, footpaths and pavement. Models which
predict beyond the line of sight often parameterize the scene with voxels or
meshes, which can be expensive to use in machine learning frameworks.
We introduce a model to predict the geometry of both visible and occluded
traversable surfaces, given a single RGB image as input. We learn from stereo
video sequences, using camera poses, per-frame depth and semantic segmentation
to form training data, which is used to supervise an image-to-image network. We
train models from the KITTI driving dataset, the indoor Matterport dataset, and
from our own casually captured stereo footage. We find that a surprisingly low
bar for spatial coverage of training scenes is required. We validate our
algorithm against a range of strong baselines, and include an assessment of our
predictions for a path-planning task.Comment: Accepted to CVPR 2020 as an oral presentatio
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