In this post, we will be looking at the paper PnPNet: End-to-End Perception and Prediction with Tracking in the Loop, by Liang et al., which was published in CVPR 2020 [1]. After defining our task and discussing some related research in this field, we will be looking at the methodology of the paper. Then we will analyze the quantitative results and have a look at the qualitative results. Finally, we will finish it off with some remarks and possible ideas for extension.
Approaches and code for identifying cacti from satellite images
Description of approaches for the APTOS medical image classification Competition
Classifying fruits using computer vision models
Vision model to classify facial expression
Recursion Cellular Image Classification
SIIM-ACR Pneumothorax Segmentation
Performance analysis of Tabular vs Vision models on Digits-MNIST dataset