most citedAudio-Visual Class-Incremental Learning

2 citations · 4 across the 4 of their papers we have counts for

collaborators

6 papers

cs.IT2024

Wideband Beamforming for Near-Field Communications with Circular Arrays

Yunhui Guo, Yang Zhang, Zhaolin Wang +1

The beamforming performance of the uniform circular array (UCA) in near-field wideband communication systems is investigated. Compared to uniform linear array (ULA), UCA exhibits u…

cs.LG2024

Inconsistency-Based Data-Centric Active Open-Set Annotation

Ruiyu Mao, Ouyang Xu, Yunhui Guo

Active learning is a commonly used approach that reduces the labeling effort required to train deep neural networks. However, the effectiveness of current active learning methods i…

cs.AI20231 cited

Towards Effective Semantic OOD Detection in Unseen Domains: A Domain Generalization Perspective

Haoliang Wang, Chen Zhao, Yunhui Guo +2

Two prevalent types of distributional shifts in machine learning are the covariate shift (as observed across different domains) and the semantic shift (as seen across different cla…

cs.CV20231 cited

VEATIC: Video-based Emotion and Affect Tracking in Context Dataset

Zhihang Ren, Jefferson Ortega, Yifan Wang +4

Human affect recognition has been a significant topic in psychophysics and computer vision. However, the currently published datasets have many limitations. For example, most datas…

cs.CV20232 cited

Audio-Visual Class-Incremental Learning

Weiguo Pian, Shentong Mo, Yunhui Guo +1

In this paper, we introduce audio-visual class-incremental learning, a class-incremental learning scenario for audio-visual video recognition. We demonstrate that joint audio-visua…

cs.RO2023

Self-Supervised Unseen Object Instance Segmentation via Long-Term Robot Interaction

Yangxiao Lu, Ninad Khargonkar, Zesheng Xu +6

We introduce a novel robotic system for improving unseen object instance segmentation in the real world by leveraging long-term robot interaction with objects. Previous approaches…