# CSE5519 Advances in Computer Vision (Topic J: 2025: Open-Vocabulary Object Detection)

## DINO-X: A Unified Vision Model for Open-World Object Detection and Understanding

Input:

- Text prompt encoder
- Visual prompt encoder
- Customized prompt encoder

Output:

- Box (object selection)
- Mask (pixel embedding map)
- Keypoint (object pose, joints estimation)
- Language (semantic understanding)

> [!TIP]
>
> This model provides the latest solution for the open-vocabulary object detection task and using Grounding-100M to break the benchmark.
>
> 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?