Unsupervised Saliency Detection
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Benchmarks
Most implemented
MOVE: Unsupervised Movable Object Segmentation and Detection
Unsupervised Salient Object Detection with Spectral Cluster Voting
Papers
Learning Accurate Segmentation Purely from Self-Supervision
Accurately segmenting objects without any manual annotations remains one of the core challenges in computer vision. In this work, we introduce Selfment, a fully self-supervised framework that segments foreground objects …
Unsupervised Saliency DetectionZero-shot GeneralizationObject DetectionTowards End-to-End Unsupervised Saliency Detection with Self-Supervised Top-Down Context
Unsupervised salient object detection aims to detect salient objects without using supervision signals eliminating the tedious task of manually labeling salient objects. To improve training efficiency, end-to-end methods…
Contrastive Learningobject-detectionObject DetectionSaliency Detection+2Unsupervised Object Localization: Observing the Background to Discover Objects
Recent advances in self-supervised visual representation learning have paved the way for unsupervised methods tackling tasks such as object discovery and instance segmentation. However, discovering objects in an image wi…
Instance SegmentationObjectObject DiscoveryObject Localization+7MOVE: Unsupervised Movable Object Segmentation and Detection
We introduce MOVE, a novel method to segment objects without any form of supervision. MOVE exploits the fact that foreground objects can be shifted locally relative to their initial position and result in realistic (undi…
Class-agnostic Object DetectionObjectobject-detectionObject Detection+7TokenCut: Segmenting Objects in Images and Videos with Self-supervised Transformer and Normalized Cut
In this paper, we describe a graph-based algorithm that uses the features obtained by a self-supervised transformer to detect and segment salient objects in images and videos. With this approach, the image patches that c…
Object DiscoverySaliency DetectionSegmentationSemantic Segmentation+6Unsupervised Salient Object Detection with Spectral Cluster Voting
In this paper, we tackle the challenging task of unsupervised salient object detection (SOD) by leveraging spectral clustering on self-supervised features. We make the following contributions: (i) We revisit spectral clu…
ClusteringObjectobject-detectionObject Detection+3