Real-time unknown object detection by using only high-level image features with Grounding DINO 1.5
Real-time unknown object detection by using only high-level image features with Grounding DINO 1.5
Grounding DINO 1.5: Advance the "Edge" of Open-Set Object Detection
arXiv paper abstract https://arxiv.org/abs/2405.10300
arXiv PDF paper https://arxiv.org/pdf/2405.10300
... introduces Grounding DINO 1.5 ... open-set object detection models developed by IDEA Research, which aims to advance the "Edge" of open-set object detection.
... two models: Grounding DINO 1.5 Pro, a high-performance model ... for stronger generalization ... across ... scenarios, and Grounding DINO 1.5 Edge ...optimized for faster speed ... in ... edge deployment.
... DINO 1.5 Pro model advances ... by scaling up the model architecture, integrating an enhanced vision backbone, and expanding the training dataset to over 20 million images with grounding annotations, thereby achieving a richer semantic understanding.
The Grounding DINO 1.5 Edge model, while designed for efficiency with reduced feature scales, maintains robust detection ... by being trained on the same comprehensive dataset.
... DINO 1.5 Pro ... attaining a 54.3 AP on the COCO detection benchmark and a 55.7 AP on the LVIS-minival zero-shot transfer benchmark, setting new records for ... object detection.
... DINO 1.5 Edge model ... optimized with TensorRT, achieves a speed of 75.2 FPS while attaining a zero-shot performance of 36.2 AP on the LVIS-minival benchmark ...
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