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Found 2 papers, 1 papers with code
Compressing Vision Transformers for Low-Resource Visual Learning
In our work, we aim to take a step toward bringing vision transformers to the edge by utilizing popular model compression techniques such as distillation, pruning, and quantization.
t-RAIN: Robust generalization under weather-aliasing label shift attacks
We present state-of-the-art pedestrian detection results on real and synthetic weather domains with best performing 82. 69 AP (snow) and 62. 31 AP (fog) respectively.
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