- Extract descriptive labels, captions, and tags
- Enable advanced semantic and object-level search
- Power downstream filtering, QA, and automation
- Improve annotation coverage and data understanding
Available Enrichment Models
Visual Layer provides a wide range of built-in models designed for diverse enrichment tasks:| Model Name | Task Type | Description |
|---|---|---|
| VL-Object-Detector | Object Detection | Identifies and localizes objects with bounding boxes and class labels. |
| VL-Image-Tagger | Multi-Class Classification | Applies multiple labels to the entire image for categorization and metadata generation. |
| VL-Object-Captioner | Object to Text | Generates short captions describing individual objects in context. |
| VL-Image-Captioner | Image to Text | Summarizes the scene or image with natural language. |
| VL-Image-Semantic Search | Semantic Image Search | Enables conceptual search over images using natural language queries. |
| VL-Object-Semantic Search | Semantic Object Search | Enables contextual search for specific objects based on semantics. |
| NVILA-Lite-2B | Image-Text-to-Text (VQA) | Efficient VQA model for visual understanding tasks across multiple frames or images. |
| Janus-Pro-1B | Image-Text-to-Text (VQA) | Autoregressive model for multi-modal reasoning and question answering. |
Some models require pre-existing labels before enrichment.
These models include:
These models include:
- Object/Image Captioners
- Semantic Search (Object or Image)
Coming Soon
These models are in development and will be available soon in the enrichment catalog:| Model Name | Description |
|---|---|
| GPT-4o | Multimodal LLM for advanced captioning and reasoning |
| Nv-grounding dino | Grounded object detection with natural language prompts |
| Neva-22B | High-performance image-to-text transformer |
| Nvclip | Lightweight vision-language model for fast embeddings |
| Qwen-VL-2B | VQA and captioning model for diverse use cases |
| Moondream2 | Compact vision-language model |
| Molmo-7B | Multimodal model for contextual enrichment |
| Advanced-Image-Search | Conceptual image retrieval using complex queries |
| Advanced-Object-Search | Enhanced semantic object retrieval |
| VL-Object-Tagger | Assigns tags at the object level across frames or images |
Want Early Access?
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Have questions or want to try out upcoming models early?
Contact us to request access or learn more.
Contact us to request access or learn more.