Unsupervised Features

Discovering Deformable Keypoint Pyramids
Jianing Qian, Anastasios Panagopoulos, Dinesh Jayaraman
ShapeCodes: Self-Supervised Feature Learning by Lifting Views to Viewgrids
Appearance-based image representations in the form of viewgrids provide a useful framework for learning self-supervised image representations by training a network to reconstruct full object shapes, or scenes.
Dinesh Jayaraman, Ruohan Gao, Kristen Grauman
Embodied Learning for Visual Recognition
Dinesh Jayaraman
Learning Image Representations Tied to Egomotion from Unlabeled Video
An agent’s continuous visual observations include information about how the world responds to its actions. This can provide an effective source of self-supervision for learning visual representations.
Dinesh Jayaraman, Kristen Grauman
Object-Centric Representation Learning from Unlabeled Videos
Unsupervised feature learning from video benefits from paying attention to changes in appearance of objects detected by an objectness measure, rather than only paying attention to the whole scene.
Ruohan Gao, Dinesh Jayaraman, Kristen Grauman
Slow and Steady Feature Analysis: Higher Order Temporal Coherence in Video
Assuming a world that mostly changes smoothly, continuous video streams entail implicit supervision that can be effectively exploited for learning visual representations.
Dinesh Jayaraman, Kristen Grauman
Learning Image Representations Tied to Egomotion
An agent’s continuous visual observations include information about how the world responds to its actions. This can provide an effective source of self-supervision for learning visual representations.
Dinesh Jayaraman, Kristen Grauman