Bbam.rar

Published at NeurIPS 2024 (Conference on Neural Information Processing Systems). Access: Available through the NeurIPS Proceedings . 3. Note on ".rar" Files

This research focuses on Weakly Supervised Learning (WSL) , where the goal is to perform complex tasks like pixel-level segmentation using only simple bounding box labels rather than expensive pixel-by-pixel annotations.

Sometimes specialized datasets related to the papers above are shared this way. BBAM.rar

It proposes the Balanced Binary Angular Margin (BBAM) loss. This loss function helps balance the "variance bias" between positive and negative samples by looking at the angle of features in a multi-label setup.

It uses a trained object detector to find the "smallest area" of an image that makes the detector produce the same result, effectively creating a map that identifies the object within the box. Published at NeurIPS 2024 (Conference on Neural Information

You can find the full PDF and supplementary materials on arXiv or through the CVF Open Access portal. 2. S²ML²-BBAM: Balanced Binary Angular Margin

Published at CVPR 2021 (Conference on Computer Vision and Pattern Recognition). Note on "

A more recent 2024 paper titled introduces a different "BBAM".