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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 126–150 of 210 papers

TitleStatusHype
Common Action Discovery and Localization in Unconstrained Videos—0
Co-Occurring of Object Detection and Identification towards unlabeled object discovery—0
Cross-Modal Distillation for 2D/3D Multi-Object Discovery from 2D Motion—0
CTRL-O: Language-Controllable Object-Centric Visual Representation Learning—0
Cycle Consistency Driven Object Discovery—0
Exploring Depth Contribution for Camouflaged Object Detection—0
Detecting and Grouping Identical Objects for Region Proposal and Classification—0
Differentiable Mathematical Programming for Object-Centric Representation Learning—0
DiffusionSeg: Adapting Diffusion Towards Unsupervised Object Discovery—0
Enforcing View-Consistency in Class-Agnostic 3D Segmentation Fields—0
Divided Attention: Unsupervised Multi-Object Discovery with Contextually Separated Slots—0
Efficient Object-centric Representation Learning with Pre-trained Geometric Prior—0
Enhancing Interpretable Object Abstraction via Clustering-based Slot Initialization—0
Enriching Visual Knowledge Bases via Object Discovery and Segmentation—0
FODVid: Flow-guided Object Discovery in Videos—0
Foreground Clustering for Joint Segmentation and Localization in Videos and Images—0
FORLA:Federated Object-centric Representation Learning with Slot Attention—0
GLASS: Guided Latent Slot Diffusion for Object-Centric Learning—0
GO-Finder: A Registration-Free Wearable System for Assisting Users in Finding Lost Objects via Hand-Held Object Discovery—0
Group-wise Deep Co-saliency Detection—0
Guided Latent Slot Diffusion for Object-Centric Learning—0
Has Anything Changed? 3D Change Detection by 2D Segmentation Masks—0
HEAP: Unsupervised Object Discovery and Localization with Contrastive Grouping—0
Hierarchical Compact Clustering Attention (COCA) for Unsupervised Object-Centric Learning—0
Hierarchical Compact Clustering Attention (COCA) for Unsupervised Object-Centric Learning—0
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