M²E-UAV is the first benchmark dataset and evaluation protocol for tiny UAV detection from a moving event camera in motion-on-motion conditions.
Film: Visual reasoning with a general conditioning layer
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AtteConDA adds attention-based conflict suppression to multi-condition diffusion models so that generated driving-scene images retain richer structural cues from the original annotations.
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M$^2$E-UAV: A Benchmark and Analysis for Onboard Motion-on-Motion Event-Based Tiny UAV Detection
M²E-UAV is the first benchmark dataset and evaluation protocol for tiny UAV detection from a moving event camera in motion-on-motion conditions.
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AtteConDA: Attention-Based Conflict Suppression in Multi-Condition Diffusion Models and Synthetic Data Augmentation
AtteConDA adds attention-based conflict suppression to multi-condition diffusion models so that generated driving-scene images retain richer structural cues from the original annotations.