5,582 research outputs found
I'm sorry to say, but your understanding of image processing fundamentals is absolutely wrong
The ongoing discussion whether modern vision systems have to be viewed as
visually-enabled cognitive systems or cognitively-enabled vision systems is
groundless, because perceptual and cognitive faculties of vision are separate
components of human (and consequently, artificial) information processing
system modeling.Comment: To be published as chapter 5 in "Frontiers in Brain, Vision and AI",
I-TECH Publisher, Viena, 200
Cross Pixel Optical Flow Similarity for Self-Supervised Learning
We propose a novel method for learning convolutional neural image
representations without manual supervision. We use motion cues in the form of
optical flow, to supervise representations of static images. The obvious
approach of training a network to predict flow from a single image can be
needlessly difficult due to intrinsic ambiguities in this prediction task. We
instead propose a much simpler learning goal: embed pixels such that the
similarity between their embeddings matches that between their optical flow
vectors. At test time, the learned deep network can be used without access to
video or flow information and transferred to tasks such as image
classification, detection, and segmentation. Our method, which significantly
simplifies previous attempts at using motion for self-supervision, achieves
state-of-the-art results in self-supervision using motion cues, competitive
results for self-supervision in general, and is overall state of the art in
self-supervised pretraining for semantic image segmentation, as demonstrated on
standard benchmarks
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