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23 lines
943 B
Markdown
23 lines
943 B
Markdown
# CSE5519 Advances in Computer Vision (Topic J: 2025: Open-Vocabulary Object Detection)
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## DINO-X: A Unified Vision Model for Open-World Object Detection and Understanding
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Input:
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- Text prompt encoder
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- Visual prompt encoder
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- Customized prompt encoder
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Output:
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- Box (object selection)
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- Mask (pixel embedding map)
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- Keypoint (object pose, joints estimation)
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- Language (semantic understanding)
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> [!TIP]
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> This model provides the latest solution for the open-vocabulary object detection task and using Grounding-100M to break the benchmark.
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> In some figures they displayed in the paper. I found some interesting differences between human recognition and CV. The fruits with smiling faces. In the object detection task, it seems that the DINO-X is not focusing on the smiling face but the fruit itself. I wonder if they can capture the abstract meaning of this representation and how it is different from human recognition, and why?
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