The World's Top-Performing Vision Model for Open-World Object Detection
The project provides examples for using DINO-X, which are hosted on DeepDataSpace.
Beyond Grounding DINO 1.5, DINO-X has several improvements, taking a step forward towards becoming a more general object-centric vision model. The highlights of the DINO-X are as follows:
✨ The Strongest Open-Set Detection Performance: DINO-X Pro set new SOTA results on zero-shot transfer detection benchmarks: 56.0 AP on COCO, 59.8 AP on LVIS-minival and 52.4 AP on LVIS-val. Notably, Notably, it scores 63.3 AP and 56.5 AP on the rare classes of LVIS-minival and LVIS-val benchmarks, improving the previous SOTA performance by 5.8 box AP and 5.0 box AP. Such a result underscores its significantly enhanced capacity for recognizing long-tailed objects.
🔥 Diverse Input Prompt and Multi-level Output Semantic Representations: DINO-X can accept text prompts, visual prompts, and customized prompts as input, and it outputs representations at various semantic levels, including bounding boxes, segmentation masks, pose keypoints, and object captions, with multiple perception heads.
🍉 Rich and Practical Capabilities: DINO-X can simultaneously support lots of highly practical tasks, including Open-Set Object Detection and Segmentation, Phrase Grounding, Visual-Prompt Counting, Pose Estimation, and Region Captioning. We further develop a universal object prompt to achieve Prompt-Free Anything Detection and Recognition.
- Refine project documentation
- Release API code and Gradio demo
We present the overall framework of DINO-X in the following image: DINO-X can accept text prompts, visual prompts, and customized prompts as input, and it can generate representations at various semantic levels, including bounding boxes, segmentation masks, pose keypoints, and object captions.
DINO-X shows a significant performance improvement compared to previous state-of-the-art methods. The following table shows that DINO-X achieves 56.0 box AP on COCO detection benchmark. On the LVIS-minival and LVIS-val benchmarks, DINO-X Pro achieves 59.8 box AP and 52.4 box AP, respectively, surpassing the previously best-performing Grounding DINO 1.6 Pro model by 2.0 AP and 1.1 AP, respectively. Notably, for the detection performance on LVIS rare classes, DINO-X achieves 63.3 AP on LVIS-minival and 56.5 AP on LVIS-val, significantly surpassing the previous SOTA Grounding DINO 1.6 Pro model by 5.8 AP and 5.0 AP, respectively, demonstrating the exceptional capability of DINO-X in long-tailed object detection scenarios.
