Dual-modality anchors from text descriptions and test-time image statistics filter views and ensemble predictions to improve test-time prompt tuning, achieving SOTA on 15 datasets.
3d object representations for fine-grained categorization
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BiCLIP recovers a structured geometric transformation from few-shot anchors to canonicalize domain features in VLMs and reports state-of-the-art results on 11 benchmarks.
LPT reduces overfitting during prompt tuning of VLMs by CLIP-based foreground filtering, a structural preservation constraint aligning features to frozen CLIP, and a hierarchical logit constraint at the output, improving generalization on base-to-novel, cross-dataset, and domain-generalization tasks
citing papers explorer
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Dual-Modality Anchor-Guided Filtering for Test-time Prompt Tuning
Dual-modality anchors from text descriptions and test-time image statistics filter views and ensemble predictions to improve test-time prompt tuning, achieving SOTA on 15 datasets.
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BiCLIP: Domain Canonicalization via Structured Geometric Transformation
BiCLIP recovers a structured geometric transformation from few-shot anchors to canonicalize domain features in VLMs and reports state-of-the-art results on 11 benchmarks.
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LPT: Less-overfitting Prompt Tuning for Vision-Language Model
LPT reduces overfitting during prompt tuning of VLMs by CLIP-based foreground filtering, a structural preservation constraint aligning features to frozen CLIP, and a hierarchical logit constraint at the output, improving generalization on base-to-novel, cross-dataset, and domain-generalization tasks