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Linearized Relative Positional Encoding
Meanwhile, it emphasizes a general paradigm for designing broadly more relative positional encoding methods that are applicable to linear transformers.
Linear Video Transformer with Feature Fixation
Therefore, we propose a feature fixation module to reweight the feature importance of the query and key before computing linear attention.
Neural Architecture Search on Efficient Transformers and Beyond
To address this issue, we propose a new framework to find optimal architectures for efficient Transformers with the neural architecture search (NAS) technique.
From Depth What Can You See? Depth Completion via Auxiliary Image Reconstruction
Specifically, we formulate image reconstruction from sparse depth as an auxiliary task during training that is supervised by the unlabelled gray-scale images.
Deep Texture and Structure Aware Filtering Network for Image Smoothing
Image smoothing is a fundamental task in computer vision, that aims to retain salient structures and remove insignificant textures.
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