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Zero-Shot Object Detection

Zero-shot object detection (ZSD) is the task of object detection where no visual training data is available for some of the target object classes.

( Image credit: Zero-Shot Object Detection: Learning to Simultaneously Recognize and Localize Novel Concepts )

Papers

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Showing 31–40 of 57 papers

TitleStatusHype
Zero-shot detection of daily objects in YCB video dataset—0
CP-DETR: Concept Prompt Guide DETR Toward Stronger Universal Object Detection—0
Eating Smart: Advancing Health Informatics with the Grounding DINO based Dietary Assistant App—0
Finding the Reflection Point: Unpadding Images to Remove Data Augmentation Artifacts in Large Open Source Image Datasets for Machine Learning—0
Frustratingly Simple but Effective Zero-shot Detection and Segmentation: Analysis and a Strong Baseline—0
Image Captioning with Unseen Objects—0
Meta-ZSDETR: Zero-shot DETR with Meta-learning—0
Multimodal Data Curation via Object Detection and Filter Ensembles—0
Multi-Modal Few-Shot Object Detection with Meta-Learning-Based Cross-Modal Prompting—0
On Hyperbolic Embeddings in 2D Object Detection—0
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