3 accepted papers
While image-text representation learning has become very popular in recent years, existing models tend to lack spatial awareness and have limited direct applicability for dense understanding tasks. For this reason, self-supervised image-only pretraining is still the go-to method for many dense visio…
From content moderation to wildlife conservation the number of applications that require models to recognize nuanced or subjective visual concepts is growing. Traditionally developing classifiers for such concepts requires substantial manual effort measured in hours days or even months to identify a…
Many computer vision tasks address the problem of scene understanding and are naturally interrelated e.g. object classification, detection, scene segmentation, depth estimation, etc. We show that we can leverage the inherent relationships among collections of tasks, as they are trained jointly, supe…