HyperAI超神経

Universal Domain Adaptation On Visda2017

評価指標

H-score
Source-free

評価結果

このベンチマークにおける各モデルのパフォーマンス結果

比較表
モデル名H-scoreSource-free
ovanet-one-vs-all-network-for-universal53.1no
boosting-novel-category-discovery-over-160.1no
do-we-really-need-to-access-the-source-data44.0yes
domain-consensus-clustering-for-universal43.0no
lead-learning-decomposition-for-source-free76.6yes
mlnet-mutual-learning-network-with69.9no
universal-domain-adaptation-via-compressive65.18no
umad-universal-model-adaptation-under-domain58.3yes
geometric-anchor-correspondence-mining-with56.4no
unified-optimal-transport-framework-for57.32no
upcycling-models-under-domain-and-category73.1yes
universal-domain-adaptation34.8no
target-semantics-clustering-via-text90.36no