Start with a photo.
End with coordinates.
Reverse Image Geolocation
Upload a photo and determine where it was taken using AI. Oceanir reads visual cues — roads, signs, buildings, terrain — to reverse-geolocate any image without metadata. Covering 103+ cities with 32.2% accuracy at 1 km.
How reverse image geolocation works
Upload
Upload an image or selected video frame with enough visible scene context. Street-level images, dashcam footage, social media screenshots, and cropped frames can work when they show roads, signs, buildings, terrain, or other geographic cues.
Match
The Orca engine extracts visual features from the image and matches them against millions of geotagged reference photographs spanning 103+ cities. A vision-language model refines the top candidates by cross-referencing architectural patterns, signage, road markings, and terrain.
Verify
Ranked location candidates appear with confidence scores, interactive map pins, and street-level comparisons. Cross-reference the results against satellite imagery and ground-truth data to confirm the location.
What makes reverse image geolocation different from forward geolocation
Direction of the query
You know the location and want images of it.
You have an image and want to find the location.
Input required
GPS coordinates, address, or place name.
A single photograph — no coordinates, no metadata.
Primary technology
Database lookup by geographic index.
Computer vision and visual feature matching against geotagged reference data.
Workflows
Finding photos of a known place (tourism, real estate listings).
Checking where an image may have been captured for journalism, insurance, legal, or evidence-review workflows.
Reverse image geolocation is the harder problem. There is no address to look up — only pixels. Oceanir's Orca engine solves this by matching visual features against a reference database of geotagged imagery covering 103+ cities across 6 continents.
Who uses reverse image geolocation
Journalists
Verify the origin of user-submitted photos and videos before publication. Confirm that images match the claimed location, detect misattributed or recycled media, and add geographic context to field reporting.
Review analysts
Review imagery from social media, field submissions, and public sources. Cross-reference AI predictions with satellite data and street-level imagery to support human verification.
Insurance teams
Validate that property damage photos correspond to the insured address. Detect geographic inconsistencies in claims documentation and flag photos taken at locations that don't match the policy.
Public-sector reviewers
Review authorized evidence photos and camera imagery. Document where submitted media may have been captured and what visible evidence supports the location claim.
Try reverse image geolocation free
Free to try. No credit card. Upload a photo and get location candidates in under 30 seconds.
Start analyzingCommon questions
Reverse image geolocation is the process of determining where a photograph was taken by analyzing the visual content of the image itself — not its metadata. Instead of starting with a known location and finding images, you start with an image and work backward to find the location. AI models read visual cues like road markings, traffic signs, architecture, and vegetation to estimate coordinates.
A reverse image search (like Google Images) finds visually similar images across the web. Reverse image geolocation goes further: it estimates the GPS coordinates where the photo was taken, even if no matching image exists online. Oceanir uses the Orca engine to match visual features against millions of geotagged reference images and return precise location candidates.
Oceanir's Orca engine achieves 32.2% accuracy at 1 km and 64.3% at 25 km on the Im2GPS3k benchmark — the highest published scores among visual geolocation systems. Coverage spans 103+ cities worldwide. Accuracy depends on the visual richness of the image: street-level photos with visible signs, buildings, and road features produce the most precise results.
No. Most photos shared on social media, messaging apps, and websites have their EXIF metadata stripped. Reverse image geolocation with Oceanir works entirely from visual content — roads, signs, architecture, terrain, vegetation, and commercial signage. No metadata, no GPS coordinates, no timestamps needed.
Journalists use it to verify the origin of user-submitted photos before publication. Insurance teams use it to confirm that claim photos match the stated property or incident context. Legal and corporate review teams use it to document whether visible scene evidence supports a location claim.
Yes. Free to try, no credit card required. Each reverse image geolocation analysis uses one credit. API access has no monthly fee and uses prepaid credits. Paid plans include Starter for occasional D3, Pro for individual verification workflows, and sales-led Enterprise plans.