Bind multiple sensory inputs for cross-modal AI understanding
ImageBind is an AI model that links together data from six different types like images, audio, and text without needing special training. This helps machines analyze information from multiple sources at once, making AI smarter and more versatile. It's particularly useful for tasks that involve understanding connections between what we see, hear, and read.
Links six data types for unified AI analysis
Find related content across images, audio, and text
Recognize tasks without prior training data
Enhance existing AI to support multiple inputs
Achieves top results across different data types
Images and video, audio, text, depth, thermal, and inertial measurement units (IMUs).
By learning a single embedding space that binds multiple sensory inputs together without explicit supervision.
Yes, the model is available on GitHub for researchers and developers.
This tool is best for:
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Recent data shows that ImageBind has 949 monthly visits (-49.1% decrease from the previous month), 89.0% bounce rate, and average 1.66 pages per visit.
Traffic is primarily driven by 6 different sources, with users from 5 countries worldwide, led by Switzerland contributing 30% of total traffic.
Monthly Visits
949
Pages per Visit
1.66
Bounce Rate
89.0%
Average Time on Site
19s
| Source | Traffic Share |
|---|---|
| Direct | 33% |
| Search | 53% |
| Social | 4% |
| Referrals | 9% |
| Paid Referrals | 1% |
| Country Name | Traffic Share |
|---|---|
 | 30% |
 | 20% |
 | 17% |
 | 16% |
 | 16% |
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