Loss Functions
Gradient Harmonizing Mechanism R
Introduced by Li et al. in Gradient Harmonized Single-stage DetectorGHM-R is a loss function designed to balance the gradient flow for bounding box refinement. The GHM first performs statistics on the number of examples with similar attributes w.r.t their gradient density and then attaches a harmonizing parameter to the gradient of each example according to the density. The modification of gradient can be equivalently implemented by reformulating the loss function. Embedding the GHM into the bounding box regression branch is denoted as GHM-R loss.
Source: Gradient Harmonized Single-stage Detector
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| General Classification | 1 | 33.33% |
| Object Detection | 1 | 33.33% |
| Philosophy | 1 | 33.33% |
Usage Over Time
Components
| Component | Type |
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|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
