Roboflow

Region Proposal Models

The one region proposal model in our catalog. Try it on your own images, free in the Roboflow Playground.

1 model · 1 open-weight · 1 free to try · prices synced Sep 11, 2026

How to Choose a Region Proposal Approach

Region proposal generates candidate object regions scored by objectness rather than class. Today it is mostly a component inside detectors, so the real question is whether you need it standalone at all.

Two-stage detectors like Faster R-CNN already include a learned Region Proposal Network; you get proposals by using the detector, not by adding a separate system. Standalone proposal generation earns its place in weakly supervised labeling, candidate narrowing before an expensive model, and research settings where recall over all plausible objects matters more than classification.

If the goal is "find everything that might be an object", class-agnostic outputs from promptable segmenters and open-vocabulary detectors now cover much of what classical proposal methods offered, with better quality. Reach for classical proposals mainly when compute is tight or a pipeline explicitly expects them.

The bottom line: Use the proposal stage built into two-stage detectors, and for standalone candidate generation consider promptable or open-vocabulary models before classical methods.

Frequently Asked Questions About Region Proposal Models

Region proposal is the task of generating candidate boxes that are likely to contain some object, scored by objectness rather than class. It began with algorithms like selective search and became the learned Region Proposal Network (RPN) inside two-stage detectors such as Faster R-CNN, where proposals are then classified and refined. Proposal quality is measured by recall: whether true objects are covered by at least one candidate. Beyond detector internals, proposals are useful for weakly supervised labeling and for narrowing expensive downstream analysis to promising regions. This page covers the one region proposal model we track, Florence-2, open-weight and free to self-host; it runs live in the Playground so you can test it on your own images.

Florence-2 is the only region proposal model in our catalog, so there is nothing here to rank it against. For fixed categories in production, a model fine-tuned on your own data typically beats any general-purpose model. Try it on your own images to see whether it fits.

Yes. The one region proposal model we track, Florence-2, is open-weight, free to self-host under its license (MIT).

Yes. You can run Florence-2 in the Roboflow Playground for free. Upload an image and see its output, no setup required.

This page lists the one region proposal models in the Roboflow Playground catalog, all of them open-weight and free to self-host; all of them run live in the Roboflow Playground on your own images. Compare licenses, parameters, and release dates side by side, or open any model page for full details.