Agentic Object Detection

Name: Agentic Object Detection
Availability: InStock
Author: LandingAI

Introducing Computer Vision Object Detection with Reasoning-Driven AI

Achieve human-like precision in object detection using text prompts—without the need for custom training.

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Reasoning-Driven Object Detection

Detect objects based on unique attributes like color, shape, and texture for smarter, more precise recognition in any scenario!

Intrinsic Attribute Recognition

Identifies objects based on their inherent properties, independent of external context.

"unripe strawberry”

Specific Object Recognition

Precisely identifies and differentiates objects within the same category based on their distinct identities.

"hex key set"

Contextual Relationship

Identifies objects based on their spatial positioning or relationship with other objects in a scene.

"daisy on top of ice cream”

Dynamic State

Detects objects based on movement, actions, or changing conditions, independent of attributes or context.

"player in mid-air"

With computer vision object detection powered by reasoning-driven AI, LandingLens eliminates the need for extensive labeling and model training, making object detection more efficient and adaptable than ever before.

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Industry Specific Use-Cases

USE CASE: Assembly Verification

capacitors

USE CASE: Workforce safety

detect person without helmet

USE CASE: Logistics

evergreen container

USE CASE: Food & Beverage

product without lid

USE CASE: Product Packaging

apple without foam covering

USE CASE: Healthcare

negative antigen test

USE CASE: Disaster Recovery

building destroyed in fire

USE CASE: Retail & Restaurant

unoccupied table

Internal Benchmarks Evaluation

LandingAI’s Agentic Object Detection significantly outperforms
systems by other leading teams.¹

Approach	Category	Recall	Precision	F1 Score
Agentic Object Detection	Agentic	77.0%	82.6%	79.7%
Microsoft Florence-2	Open Set Object Detection	43.4%	36.6%	39.7%
Google OWLv2	Open Set Object Detection	81.0%	29.5%	43.2%
AliBaba Qwen2.5-VL-7B-Instruct	LMM	26.0%	54.0%	35.1%

¹ Benchmark consists of images from Pixmo datasets and annotated internally with bounding box, object prompts and/or reference expressions.

What’s Coming

We’re excited to share this Agentic Object Detection milestone with you.
While it’s a significant step forward, we’re committed to ongoing improvements in accuracy and speed.

Future plans include adding object tracking, multiple object types detection, and video support.
We invite you to explore our APIs and create innovative projects.

Join our VisionAgent Discord Community to share your feedback and cool projects.

Stay tuned for updates and happy building!

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