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Found 5 papers, 1 papers with code
DMKD: Improving Feature-based Knowledge Distillation for Object Detection Via Dual Masking Augmentation
Recent mainstream masked distillation methods function by reconstructing selectively masked areas of a student network from the feature map of its teacher counterpart.
Holistic Prototype Attention Network for Few-Shot VOS
Existing methods have demonstrated that the domain agent-based attention mechanism is effective in FSVOS by learning the correlation between support images and query frames.
AMD: Adaptive Masked Distillation for Object Detection
As a general model compression paradigm, feature-based knowledge distillation allows the student model to learn expressive features from the teacher counterpart.
Real-time Human Activity Recognition Using Conditionally Parametrized Convolutions on Mobile and Wearable Devices
For deep learning, improvements in performance have to heavily rely on increasing model size or capacity to scale to larger and larger datasets, which inevitably leads to the increase of operations.
Layer-wise training convolutional neural networks with smaller filters for human activity recognition using wearable sensors
A set of lower-dimensional filters is used as Lego bricks to be stacked for conventional filters, which does not rely on any special network structure.
