Object Detection using Vicreg and RetinaNet
Example 1
For this project we aim at carrying out an object detection task with variable sized input. We first researched on recent state-of-the-art methods, and then performed our downstream task using VICreg (Variance-Invariance-Covariance Regularization) (Bardes et al., 2021) to pretrain our ResNet backbone and RetinaNet (Lin et al., 2017) to finetune on labeled images. Our team achieved a mAP score of 0.125 on validation dataset and we identified several ways to improve upon our current approach as well as proposed novel methods that we should try out.