We introduce a multi-task setting for PCoTT A, which is practical and realistic, handling multiple tasks within one unified model during the continual adaptation.

The remarkable capability of over-parameterised neural networks to generalise effectively has been explained by invoking a "simplicity bias": neural networks prevent overfitting by initially learning simple classifiers before progressing to

Predicting 3D geometry in dynamic scenes is a challenging problem. In this problem setup, we are given access to multiple images of a scene taken sequentially, e.g., from a monocular video

A vision model with general-purpose object-level 3D understanding should be capable of inferring both 2D ( e.g., class name and bounding box) and 3D information ( e.g., 3D location and 3D viewpoint) for arbitrary rigid objects in natural