Search Results for author:
Found 7 papers, 4 papers with code
Active Generalized Category Discovery
Generalized Category Discovery (GCD) is a pragmatic and challenging open-world task, which endeavors to cluster unlabeled samples from both novel and old classes, leveraging some labeled data of old classes.
Dual Mean-Teacher: An Unbiased Semi-Supervised Framework for Audio-Visual Source Localization
Audio-Visual Source Localization (AVSL) aims to locate sounding objects within video frames given the paired audio clips.
Cross Pseudo-Labeling for Semi-Supervised Audio-Visual Source Localization
Audio-Visual Source Localization (AVSL) is the task of identifying specific sounding objects in the scene given audio cues.
Open-world Machine Learning: A Review and New Outlooks
This paper aims to provide a comprehensive introduction to the emerging open-world machine learning paradigm, to help researchers build more powerful AI systems in their respective fields, and to promote the development of artificial general intelligence.
Towards Trustworthy Dataset Distillation
By distilling both InD samples and outliers, the condensed datasets are capable to train models competent in both InD classification and OOD detection.
Rethinking Pretraining as a Bridge from ANNs to SNNs
In this work, a new SNN training paradigm is proposed by combining the concepts of the two different training methods with the help of the pretrain technique and BP-based deep SNN training mechanism.
