Ev-DTAD improves event-based object detection accuracy and speed by using hierarchical temporal aggregation at the representation level and frequency-aware hypergraph fusion at the model level.
Unsupervised event-based learning of optical flow, depth, and egomotion
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Bi-CMPStereo uses bidirectional prompting to project event and frame data into each other's domains, creating aligned representations for improved cross-modal stereo matching.
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Rethinking Event-Based Object Dtection through Representation-Level Temporal Aggregation and Model-Level Hypergraph Reasoning
Ev-DTAD improves event-based object detection accuracy and speed by using hierarchical temporal aggregation at the representation level and frequency-aware hypergraph fusion at the model level.
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Bidirectional Cross-Modal Prompting for Event-Frame Asymmetric Stereo
Bi-CMPStereo uses bidirectional prompting to project event and frame data into each other's domains, creating aligned representations for improved cross-modal stereo matching.