Despite the remarkable progress of Fine-grained visual classification (FGVC) with years of
history, it is still limited to recognizing 2 images. Recognizing objects in the physical world …

In the quest for unveiling novel categories at test time, we confront the inherent limitations of
traditional supervised recognition models that are restricted by a predefined category set …

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 …

Abstract Neural Radiance Fields (NeRF) have been extensively explored as a leading
approach for modeling and representing 3D data across various domains. Their ability to …

Because of its use in practice, open-world object detection (OWOD) has gotten a lot of
attention recently. The challenge is how can a model detect novel classes and then …

Probabilistic Notations. We denote the input random variable with X and the category
random variable with C. The category code random variable, which we define as the …

Any classification or regression model needs access to the same features and input that
were utilized to train the model. However in real world scenarios, several models are in …