arXiv Machine Learning By Mohammad Fahes, Tuan-Hung Vu, Andrei Bursuc, Patrick P\'erez, Raoul de Charette

Domain Adaptation with a Single Vision-Language Embedding

Read the original on arXiv Machine Learning →

arXiv:2410. 21361v2 Announce Type: replace-cross Abstract: Domain adaptation has been extensively investigated in computer vision but still requires access to target data at the training time, which might be difficult to obtain in real-world autonomous driving scenarios, especially under rare or adverse conditions.

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arXiv Machine Learning
Jun 9

Zero-Shot Semantic Re-Identification for Autonomous Driving: A VLM Baseline Study

arXiv:2606. 09362v1 Announce Type: cross Abstract: Re-Identification (ReID) in autonomous driving is typically formulated as a visual matching problem, where observations of vehicles, pedestrians, and cyclists are associated across time, frames, or camera views using learned appearance embeddings, often complemented by motion, geometric, or multimodal cues.

By Eduardo Borges, Manuel Abreu, Lu\'is Garrote, Urbano J. Nunes