SearchAD is a large-scale semantic image retrieval benchmark for rare driving scenarios that supports text-to-image and image-to-image tasks and shows text-based methods outperform image-based ones while overall performance stays limited.
OpenAD: Open-world au- tonomous driving benchmark for 3D object detection
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DSAA improves fine-grained open-vocabulary object detection by injecting attribute priors via APA in text embeddings, modulating K/V vectors in BERT, and using an attribute-aware contrastive loss, with gains shown on the FG-OVD benchmark.
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SearchAD: Large-Scale Rare Image Retrieval Dataset for Autonomous Driving
SearchAD is a large-scale semantic image retrieval benchmark for rare driving scenarios that supports text-to-image and image-to-image tasks and shows text-based methods outperform image-based ones while overall performance stays limited.
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DSAA: Dual-Stage Attribute Activation for Fine-grained Open Vocabulary Detection
DSAA improves fine-grained open-vocabulary object detection by injecting attribute priors via APA in text embeddings, modulating K/V vectors in BERT, and using an attribute-aware contrastive loss, with gains shown on the FG-OVD benchmark.