Images of the natural world collected by a variety of cameras from drones to individual
phones are increasingly abundant sources of biological information. There is an explosion …

Due to the expensive costs of collecting labels in multi-label classification datasets, partially
annotated multi-label classification has become an emerging field in computer vision. One …

Visual category discovery methods aim to find novel categories in unlabeled visual data. At
training time, a set of labeled and unlabeled images are provided, where the labels …

Open-vocabulary object detection (OvOD) has transformed detection into a language-
guided task empowering users to freely define their class vocabularies of interest during …

In recent years, considerable work has been devoted to explaining predictive, deep learning-
based models, and in turn how to evaluate explanations. An important class of evaluation …

Images are increasingly becoming the currency for documenting biodiversity on the planet,
providing novel opportunities for accelerating scientific discoveries in the field of organismal …

Seagrass meadows serve as critical carbon sinks, but estimating the amount of carbon they
store requires knowledge of the seagrass species present. Underwater and surface vehicles …

While remarkable success has been achieved in weakly-supervised object localization
(WSOL), current frameworks are not capable of locating objects of novel categories in open …

With the advent of billion-parameter foundation models, efficient fine-tuning has become
increasingly important for the adaptation of models to downstream tasks. However …

Open-set recognition (OSR) methods aim to identify whether or not a test example belongs
to a category ob-served during training. Depending on how visually sim-ilar a test example …