research
∙
07/03/2023
Towards Building Self-Aware Object Detectors via Reliable Uncertainty Quantification and Calibration
The current approach for testing the robustness of object detectors suff...
share
research
∙
01/03/2023
Correlation Loss: Enforcing Correlation between Classification and Localization
Object detectors are conventionally trained by a weighted sum of classif...
research
∙
10/19/2021
Mask-aware IoU for Anchor Assignment in Real-time Instance Segmentation
This paper presents Mask-aware Intersection-over-Union (maIoU) for assig...
research
∙
07/24/2021
Rank Sort Loss for Object Detection and Instance Segmentation
We propose Rank Sort (RS) Loss, as a ranking-based loss function to ...
research
∙
11/21/2020
One Metric to Measure them All: Localisation Recall Precision (LRP) for Evaluating Visual Detection Tasks
Despite being widely used as a performance measure for visual detection ...
research
∙
09/28/2020
A Ranking-based, Balanced Loss Function Unifying Classification and Localisation in Object Detection
We propose average Localization-Recall-Precision (aLRP), a unified, boun...
research
∙
09/21/2019
Generating Positive Bounding Boxes for Balanced Training of Object Detectors
Two-stage deep object detectors generate a set of regions-of-interest (R...
research
∙
08/31/2019
Imbalance Problems in Object Detection: A Review
In this paper, we present a comprehensive review of the imbalance proble...
research
∙
07/04/2018
