Papers › COSMo: CLIP Talks on Open-Set Multi-Target Domain Adaptation
COSMo: CLIP Talks on Open-Set Multi-Target Domain Adaptation
Munish Monga, Sachin Kumar Giroh, Ankit Jha, Mainak Singha, Biplab Banerjee, Jocelyn Chanussot
Multi-Target Domain Adaptation (MTDA) entails learning domain-invariant information from a single source domain and applying it to multiple unlabeled target domains. Yet, existing MTDA methods predominantly focus on addressing domain shifts within visual features, often overlooking semantic features and struggling to handle unknown classes, resulting in what is known as Open-Set (OS) MTDA. While large-scale vision-language foundation models like CLIP show promise, their potential for MTDA remains largely unexplored. This paper introduces COSMo, a novel method that learns domain-agnostic prompts through source domain-guided prompt learning to tackle the MTDA problem in the prompt space. By leveraging a domain-specific bias network and separate prompts for known and unknown classes, COSMo effectively adapts across domain and class shifts. To the best of our knowledge, COSMo is the first method to address Open-Set Multi-Target DA (OSMTDA), offering a more realistic representation of real-world scenarios and addressing the challenges of both open-set and multi-target DA. COSMo demonstrates an average improvement of 5.1% across three challenging datasets: Mini-DomainNet, Office-31, and Office-Home, compared to other related DA methods adapted to operate within the OSMTDA setting. Code is available at: https://github.com/munish30monga/COSMo
Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Open-Set Multi-Target Domain Adaptation | MiniDomainNet | COSMo | H-Score | 81.84 | #1 of 1 | Archive leaderboard | report |
| Open-Set Multi-Target Domain Adaptation | Office-31 | COSMo | H-Score | 90.01 | #1 of 1 | Archive leaderboard | report |
| Open-Set Multi-Target Domain Adaptation | Office-Home | COSMo | H-Score | 83.04 | #1 of 1 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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