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Found 4 papers, 2 papers with code
MobileTL: On-device Transfer Learning with Inverted Residual Blocks
MobileTL trains the shifts for internal normalization layers to avoid storing activation maps for the backward pass.
FOX-NAS: Fast, On-device and Explainable Neural Architecture Search
Neural architecture search can discover neural networks with good performance, and One-Shot approaches are prevalent.
Learning from 2D: Contrastive Pixel-to-Point Knowledge Transfer for 3D Pretraining
Most 3D neural networks are trained from scratch owing to the lack of large-scale labeled 3D datasets.
A Unified Point-Based Framework for 3D Segmentation
We present a new unified point-based framework for 3D point cloud segmentation that effectively optimizes pixel-level features, geometrical structures and global context priors of an entire scene.
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