Coordinate Based Region Pointing And Gaze Detection

via “coordinate-based region pointing and gaze detection”

Tiny vision-language model for edge devices.

Unique: Region encoder subsystem directly outputs coordinate embeddings that map to pixel space, enabling end-to-end coordinate prediction without separate regression heads; coordinate transformations handle conversion between normalized and absolute coordinates, enabling flexible output formats.

vs others: Integrated into single model without separate pointing or gaze detection modules; enables spatial reasoning without training custom coordinate regression networks.

via “bounding-box-coordinate-prompting”

A free DeepLearning.AI short course on how to prompt computer vision models with natural language, bounding boxes, segmentation masks, coordinate points, and other images.

Unique: Bridges the gap between traditional computer vision coordinate systems and natural language prompting by teaching how to embed spatial notation directly into conversational prompts, enabling hybrid human-readable + machine-parseable region specification

vs others: More practical than academic computer vision courses because it focuses on how to communicate coordinates to LLMs rather than how to compute them, addressing the emerging use case of LLM-based visual reasoning with spatial constraints