Deep Predictive Coding Networks for Video Prediction and Unsupervised\n Learning
Abstract
While great strides have been made in using deep learning algorithms to solve\nsupervised learning tasks, the problem of unsupervised learning - leveraging\nunlabeled examples to learn about the structure of a domain - remains a\ndifficult unsolved challenge. Here, we explore prediction of future frames in a\nvideo sequence as an unsupervised learning rule for learning about the\nstructure of the visual world. We describe a predictive neural network\n("PredNet") architecture that is inspired by the concept of "predictive coding"\nfrom the neuroscience literature. These networks learn to predict future frames\nin a video sequence, with each layer in the network making local predictions\nand only forwarding deviations from those predictions to subsequent network\nlayers. We show that these networks are able to robustly learn to predict the\nmovement of synthetic (rendered) objects, and that in doing so, the networks\nlearn internal representations that are useful for decoding latent object\nparameters (e.g. pose) that support object recognition with fewer training\nviews. We also show that these networks can scale to complex natural image\nstreams (car-mounted camera videos), capturing key aspects of both egocentric\nmovement and the movement of objects in the visual scene, and the\nrepresentation learned in this setting is useful for estimating the steering\nangle. Altogether, these results suggest that prediction represents a powerful\nframework for unsupervised learning,…
Read the paper
Related studies
- Regulation of nucleolus assembly by non-coding RNA polymerase II transcripts
- For a Healthy Histone Code, a Little SUMO in the Tail Keeps the Acetyl Away
- Discovering a binary CTCF code with a little help from BORIS
- Article Commentary: Stabilizing the Code–-Methods to Preserve RNA Prove Their Worth
- Foreword to the Special Issue for the RINTC (The Implicit Seismic Risk of Code-Conforming Structures) Project
- Commentary: Promoting Health and Well-being in Pediatric Primary Care Settings: Using Health and Behavior Codes at Routine Well-child Visits
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.