Auto Annotation

• Grounding DINO – Object Detection (OD)

  • Used for automated object detection annotations.

  • Provides bounding box generation based on visual grounding and textual prompts.

  • Supports multi-object detection in complex scenes.

  • Improves annotation speed and accuracy with minimal manual intervention.

  • Integrates seamlessly with QpiAI’s auto-annotation pipeline.

  • Ideal for datasets requiring precise localization of multiple objects.

• Grounding SAM – Segmentation (SAM)

  • Used for instance segmentation annotations.

  • Converts object boundaries into pixel-level masks for detailed labeling.

  • Enables high-quality annotations for tasks like medical imaging, autonomous vision, and industrial inspection.

  • Reduces manual polygon drawing effort significantly.

• Grounding DINO-Large – Advanced Object Detection (OD)

  • A more powerful version of Grounding DINO for complex and large-scale object detection tasks.

  • Handles dense scenes, small objects, and multiple overlapping instances effectively.

  • Suitable for datasets where standard DINO might underperform due to complexity.

  • Improves recall and precision for fine-grained categories.

  • Provides robust support for domain adaptation and custom vocabulary grounding.

  • Enables pose estimation and landmark detection tasks.

  • Supports body, hand, and facial keypoints depending on dataset requirements.

  • Can be used alongside DINO or SAM outputs for composite annotation workflows.

  • Facilitates downstream applications such as gesture recognition, motion tracking, and activity analysis.

  • Upcoming integration with hybrid annotation pipelines in QpiAI Pro.

• Qwen3-vl-4b (OD)

  • Integrates object recognition, unified multimodal analysis.

  • Handles dense captions, referring expression comprehension, and visual question answering (VQA) with high accuracy.

  • Supports complex scene parsing and alignment across images and textual descriptions.

  • Enables interactive multimodal chat, annotation guidance, and context-aware labeling within QpiAI Pro.

  • Compatible with Grounding DINO, SAM, and RT-DETR for composite detection–captioning pipelines.

  • Upcoming extensions include video-grounded dialogue, temporal reasoning, and dynamic visual tracking capabilities.