Counting in the Wild
In this paper we explore the scenario of learning to count multiple instances of objects from images that have been dot annotated through crowdsourcing. Specifically, we work with a large and challenging image dataset of penguins in the wild, for which tens of thousands of volunteer annotators have placed dots on instances of penguins in tens of thousands of images. The dataset, introduced and released with this paper, shows such a high degree of object occlusion and scale variation that individual object detection or simple counting density estimation is not able to estimate the bird counts reliably.
ECCV