Better image segmentation by using image preprocessing network for a model by with ION
Better image segmentation by using image preprocessing network for a model by with ION
Building Resilience to Out-of-Distribution Visual Data via Input Optimization and Model Finetuning
arXiv paper abstract https://arxiv.org/abs/2211.16228
arXiv PDF paper https://arxiv.org/ftp/arxiv/papers/2211/2211.16228.pdf
A ... challenge in machine learning is resilience to out-of-distribution data ... that exists outside of the distribution of a model's training data.
Training is often performed using limited ... datasets and so when a model is deployed there is often a significant distribution shift as ... cases ... not included in the training ... are encountered.
... propose the Input Optimisation Network, an image preprocessing model that learns to optimise input data for a specific target vision model.
... investigate ... out-of-distribution scenarios in ... semantic segmentation for autonomous vehicles, comparing an Input Optimisation based solution to existing approaches of finetuning the target model with augmented training data and an adversarially trained preprocessing model.
... demonstrate ... performance ... comparable to that of a finetuned model, and subsequently that a combined approach, whereby an input optimization network is optimised to target a finetuned model, delivers superior performance to either method in isolation.
... propose a joint optimisation approach, in which input optimization network and target model are trained simultaneously, which ... demonstrate achieves significant further performance gains ...
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