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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
Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object DetectionCode5
Frustratingly Simple but Effective Zero-shot Detection and Segmentation: Analysis and a Strong Baseline—0
Resolving Semantic Confusions for Improved Zero-Shot DetectionCode1
Bridging the Gap between Object and Image-level Representations for Open-Vocabulary DetectionCode2
ELEVATER: A Benchmark and Toolkit for Evaluating Language-Augmented Visual ModelsCode4
Multi-Modal Few-Shot Object Detection with Meta-Learning-Based Cross-Modal Prompting—0
On Hyperbolic Embeddings in 2D Object Detection—0
From Node to Graph: Joint Reasoning on Visual-Semantic Relational Graph for Zero-Shot DetectionCode0
Robust Region Feature Synthesizer for Zero-Shot Object DetectionCode1
Grounded Language-Image Pre-trainingCode2
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