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Found 3 papers, 2 papers with code
A Simple and Efficient Baseline for Zero-Shot Generative Classification
While recent zero-shot diffusion-based classifiers have made performance advancement on benchmark datasets, they still suffered badly from extremely slow classification speed (e. g., ~1000 seconds per classifying single image on ImageNet).
Entropy Loss: An Interpretability Amplifier of 3D Object Detection Network for Intelligent Driving
Entropy Loss is formulated based on the functionality of feature compression networks within the perception model.
Eloss in the way: A Sensitive Input Quality Metrics for Intelligent Driving
With the increasing complexity of the traffic environment, the importance of safety perception in intelligent driving is growing.
Ranked #9 on
3D Object Detection
on KITTI Cyclists Moderate
