3 accepted papers
Open world perception expands traditional closed-set frameworks, which assume a predefined set of known categories, to encompass dynamic real-world environments. Open World Object Detection (OWOD) and Open Vocabulary Object Detection (OVD) are two main research directions, each addressing unique cha…
Open-World Object Detection (OWOD) has garnered widespread attention due to its ability to recall unannotated objects. Existing works generate pseudo-labels for the model using heuristic priors, which limits the model’s performance. In this paper, we leverage the knowledge of the large-scale visual…
Open-World Object Detection (OWOD) is a challenging task that requires the detector to identify unlabeled objects and continuously demands the detector to learn new knowledge based on existing ones. Existing methods primarily focus on recalling unknown objects, neglecting to explore the reasons behi…