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Beyond the Limitation of Monocular 3D Detector via Knowledge Distillation
Moreover, we construct a depth-guided matrix by the predicted depth gap of teacher and student to facilitate the model to learn more knowledge of farther objects in prediction level distillation.
1% VS 100%: Parameter-Efficient Low Rank Adapter for Dense Predictions
Fine-tuning large-scale pre-trained vision models to downstream tasks is a standard technique for achieving state-of-the-art performance on computer vision benchmarks.
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