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Found 5 papers, 1 papers with code
Dataset Distillation using Neural Feature Regression
Dataset distillation can be formulated as a bi-level meta-learning problem where the outer loop optimizes the meta-dataset and the inner loop trains a model on the distilled data.
Stochastic Whitening Batch Normalization
BN uses scaling and shifting to normalize activations of mini-batches to accelerate convergence and improve generalization.
BoxNet: A Deep Learning Method for 2D Bounding Box Estimation from Bird's-Eye View Point Cloud
We present a learning-based method to estimate the object bounding box from its 2D bird's-eye view (BEV) LiDAR points.
Adaptive Hierarchical Down-Sampling for Point Cloud Classification
While several convolution-like operators have recently been proposed for extracting features out of point clouds, down-sampling an unordered point cloud in a deep neural network has not been rigorously studied.
Sparse Representation-based Image Quality Assessment
This sparse strategy is employed because it is known to generate basis vectors that are qualitatively similar to the receptive field of the simple cells present in the mammalian primary visual cortex.
