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 )
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Greatest papers with code
Zero-Shot Object Detection: Learning to Simultaneously Recognize and Localize Novel Concepts
We hypothesize that this setting is ill-suited for real-world applications where unseen objects appear only as a part of a complex scene, warranting both the `recognition' and `localization' of an unseen category.
Polarity Loss for Zero-shot Object Detection
• salman-h-khan/PL-ZSD_Release
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This setting gives rise to the need for correct alignment between visual and semantic concepts, so that the unseen objects can be identified using only their semantic attributes.
METRIC LEARNING ZERO-SHOT LEARNING ZERO-SHOT OBJECT DETECTION
Zero-Shot Object Detection by Hybrid Region Embedding
Object detection is considered as one of the most challenging problems in computer vision, since it requires correct prediction of both classes and locations of objects in images.