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Found 4 papers, 2 papers with code
Unsupervised Multi-object Segmentation by Predicting Probable Motion Patterns
We propose a new approach to learn to segment multiple image objects without manual supervision.
Guess What Moves: Unsupervised Video and Image Segmentation by Anticipating Motion
Motion, measured via optical flow, provides a powerful cue to discover and learn objects in images and videos.
Ranked #4 on
Unsupervised Object Segmentation
on SegTrack-v2
Unsupervised Part Discovery from Contrastive Reconstruction
First, we construct a proxy task through a set of objectives that encourages the model to learn a meaningful decomposition of the image into its parts.
Ranked #1 on
Unsupervised Keypoint Estimation
on CUB
The Curious Layperson: Fine-Grained Image Recognition without Expert Labels
We then train a fine-grained textual similarity model that matches image descriptions with documents on a sentence-level basis.
