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Object Discovery

Object Discovery is the task of identifying previously unseen objects.

Source: Unsupervised Object Discovery and Segmentation of RGBD-images

Papers

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Showing 51–75 of 210 papers

TitleStatusHype
Object Discovery via Contrastive Learning for Weakly Supervised Object DetectionCode1
Large-Scale Unsupervised Object DiscoveryCode1
Learning Open-World Object Proposals without Learning to ClassifyCode1
Object-Centric Learning for Real-World Videos by Predicting Temporal Feature SimilaritiesCode1
Vector-Quantized Vision Foundation Models for Object-Centric LearningCode1
Co-Occurring of Object Detection and Identification towards unlabeled object discovery—0
Active Image Segmentation Propagation—0
Language-Mediated, Object-Centric Representation Learning—0
FORLA:Federated Object-centric Representation Learning with Slot Attention—0
Appearance Fusion of Multiple Cues for Video Co-localization—0
Foreground Clustering for Joint Segmentation and Localization in Videos and Images—0
GLASS: Guided Latent Slot Diffusion for Object-Centric Learning—0
FODVid: Flow-guided Object Discovery in Videos—0
Common Action Discovery and Localization in Unconstrained Videos—0
Label-Efficient 3D Object Detection For Road-Side Units—0
Large Scale Novel Object Discovery in 3D—0
Co-localization with Category-Consistent Features and Geodesic Distance Propagation—0
Enriching Visual Knowledge Bases via Object Discovery and Segmentation—0
Enhancing Interpretable Object Abstraction via Clustering-based Slot Initialization—0
Co-localization in Real-World Images—0
Betrayed by Motion: Camouflaged Object Discovery via Motion Segmentation—0
K-means for unsupervised instance segmentation using a self-supervised transformer—0
Efficient Object-centric Representation Learning with Pre-trained Geometric Prior—0
Divided Attention: Unsupervised Multi-Object Discovery with Contextually Separated Slots—0
Agile Depth Sensing Using Triangulation Light Curtains—0
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