SPACE: Semantic Projection and Alignment of CLIP Embeddings for Domain Adaptation

arXiv:2609.23248 · cs.CV · Submitted 2026-09-19 · Read on arXiv

cs.CV

Submitted: 2026-09-19

Updated: 2026-09-19

Terminology

Adaptation — 24× in this paper · explained in 1 episode
Alignment — 20× in this paper · explained in 1 episode
Domain Adaptation — 18× in this paper · explained in 5 episodes
Unsupervised Domain Adaptation — 10× in this paper
Pseudo-labeling — 7× in this paper · explained in 3 episodes
Benchmark — 5× in this paper · explained in 2 episodes
Domain Shift — 5× in this paper · explained in 4 episodes
Embeddings — 5× in this paper · explained in 2 episodes
Core — 4× in this paper · explained in 2 episodes
Pseudo-labels — 4× in this paper · explained in 2 episodes
Semantic Alignment — 4× in this paper · explained in 3 episodes
Accuracy — 3× in this paper · explained in 1 episode
Distillation — 3× in this paper · explained in 2 episodes
Cosine Similarity — 2× in this paper · explained in 3 episodes
Generalization — 2× in this paper · explained in 13 episodes
Loss Function — 2× in this paper · explained in 2 episodes
Singular Value Decomposition — 2× in this paper
Adam — 1× in this paper · explained in 2 episodes
Contrastive Language-Image Pre-training — 1× in this paper
Hilbert Space — 1× in this paper · explained in 2 episodes
Knowledge Distillation — 1× in this paper · explained in 11 episodes
Maximum Mean Discrepancy — 1× in this paper
Regularization — 1× in this paper · explained in 3 episodes
Reproducing Kernel Hilbert Space (RKHS) — 1× in this paper · explained in 3 episodes
Robustness — 1× in this paper · explained in 5 episodes
Singular Value Decomposition (SVD) — 1× in this paper · explained in 2 episodes
Transferability — 1× in this paper · explained in 4 episodes
Vision-language models — 1× in this paper · explained in 2 episodes

Sources

VisDA: The Visual Domain Adaptation Challenge

Terminology

Sources

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