Patrick Pérez

MOCA: Self-supervised Representation Learning by Predicting Masked Online Codebook Assignments

2023 · arXiv (Cornell University)

Self-supervised learning can be used for mitigating the greedy needs of Vision Transformer networks for very large fully-annotated datasets. Different classes of self-supervised learning offer representations with either good contextual reasoning properties, e.g., using masked …

Reliability in Semantic Segmentation: Can We Use Synthetic Data?

2023 · arXiv (Cornell University)

Assessing the robustness of perception models to covariate shifts and their ability to detect out-of-distribution (OOD) inputs is crucial for safety-critical applications such as autonomous vehicles. By nature of such applications, however, the relevant data …