What Images Cannot Say: Language-Guided Olfactory Representation Learning
Images tell us what a scene looks like, but rarely what it would feel like to be there. While recent datasets pair visual scenes with electronic-nose measurements, aligning smell signals with images remains challenging because many olfactory cues arise from contextual environmental factors that are not directly visible in pixels. We introduce SCENT, a multimodal framework that uses language guidance as a semantic bridge between vision and olfaction. Our approach leverages Vision-Language Models (VLMs) to generate scene descriptors capturing objects, environmental context, and plausible ambient
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Paper → model → repo connections mined from source citations (Tier-1 exact match).
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- LinkedLinked via arxiv author · 85%Eleftherios Tsonis →
“What Images Cannot Say: Language-Guided Olfactory Representation Learning”
- LinkedLinked via arxiv author · 85%Junxi Wang →
“What Images Cannot Say: Language-Guided Olfactory Representation Learning”
- LinkedLinked via arxiv author · 85%Vicky Kalogeiton →
“What Images Cannot Say: Language-Guided Olfactory Representation Learning”
- FuzzyOverlapping authors or contributors · 62%bytedance/deer-flow →
“Shared author/contributor keys: wang”
- FuzzyOverlapping authors or contributors · 62%ray-project/ray →
“Shared author/contributor keys: wang”
- FuzzySimilar title/name (fuzzy) · 59%aymericdamien/TopDeepLearning →
“Fuzzy title match (0.73): “What Images Cannot Say: Language-Guided Olfactory Representa” ≈ “aymericdamien/TopDeepLearning””