Segment dark images by using RAW image data reducing feature noise with LIS
- morrislee
- Apr 28, 2023
- 1 min read
Segment dark images by using RAW image data reducing feature noise with LIS
Instance Segmentation in the Dark
arXiv paper abstract https://arxiv.org/abs/2304.14298
arXiv PDF paper https://arxiv.org/pdf/2304.14298.pdf
Project page https://github.com/Linwei-Chen/LIS
Existing instance segmentation techniques are primarily tailored for high-visibility inputs, but their performance significantly deteriorates in extremely low-light environments.
... The proposed method is motivated by the observation that noise in low-light images introduces high-frequency disturbances to the feature maps of neural networks, thereby significantly degrading performance.
... propose a novel learning method that relies on an adaptive weighted downsampling layer, a smooth-oriented convolutional block, and disturbance suppression learning.
These components effectively reduce feature noise during downsampling and convolution operations, enabling the model to learn disturbance-invariant features.
... discover that high-bit-depth RAW images can better preserve richer scene information in low-light conditions ... can be critical for ... segmentation.
... without any image preprocessing, ... achieve satisfactory performance on instance segmentation in very low light (4% AP higher than state-of-the-art competitors) ...
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