Feb 3, 2025 · GIoU, DIoU and CIoU were introduced to address limitations of the basic Intersection over Union (IoU) loss, which is commonly used in object detection for bounding box regression.

Compute Complete Intersection over Union (CIOU) between two sets of boxes. Both sets of boxes are expected to be in (x1, y1, x2, y2) format with 0 <= x1 < x2 and 0 <= y1 < y2.

Jun 13, 2023 · This article will focus on IoU loss functions (GIoU loss, DIoU loss, and CIoU loss). But first, we will gain an intuitive understanding of the loss function for object detection in general.

DIoU and CIoU losses are incorporated into state-of-the-art detection algorithms, including YOLO v3, SSD and Faster R-CNN. The details of implementation and comparison can be respectively found in …

Oct 10, 2024 · Each variant — GIoU, DIoU, and CIoU — brings something unique to the table and addresses the shortcomings of the vanilla IoU’s in non-overlapping, distant, or shape-sensitive cases.

GIoU vs DIoU vs CIoU | Losses | Essentials of Object Detection Kapil Sachdeva 11.2K subscribers Subscribe

CIoU (Complete IoU): CIoU further enhances DIoU by introducing additional terms to account for aspect ratio discrepancies and box overlap. It addresses the limitations of previous metrics by considering …

First, Complete-IOU (CIOU) was introduced to improve the K-means clustering algorithm, and then an anchor of appropriate size...

Source code for torchvision.ops.ciou_loss import torch from ..utils import _log_api_usage_once from ._utils import _upcast_non_float from .diou_loss import _diou_iou_loss

Jan 19, 2024 · This paper introduces the commonly used loss function IoU, GIoU, DIou and CIoU. IoU IoU is the most widely used detection frame loss function, and most detection algorithms use this …