Shypd.aiThe largest open index of AI toolsSNIPER is an open-source research tool for efficient multi-scale object detection and instance-level segmentation. It uses selective processing of context regions to speed up multi-scale training and inference.
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SNIPER, also known as AutoFocus, is an efficient multi-scale training and inference algorithm designed for instance-level recognition tasks such as object detection and instance-level segmentation. It significantly speeds up multi-scale training by selectively processing context regions around ground-truth objects, called 'chips', operating on low-resolution data. This memory-efficient design allows SNIPER to benefit from Batch Normalization and larger batch-sizes on a single GPU. AutoFocus, the inference component, employs a coarse-to-fine approach, processing only regions likely to contain small objects at finer scales using 'FocusPixels' to generate compact 'FocusChips'. The tool supports half-precision training with no loss in accuracy and offers fast inference speeds, making it suitable for advanced computer vision research and development.
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