5 accepted papers
Depression represents a global mental health challenge requiring efficient and reliable automated detection methods. Current Transformer- or Graph Neural Networks (GNNs)-based multimodal depression detection methods face significant challenges in modeling individual differences and cross-modal tempo
Hybrid image retrieval is a significant task for a wide range of applications. In this scenario, the hybrid query for searching images consists of a reference image and a text modifier. The reference image provides a vital visual context and displays some semantic details, while the text modifier sp…
Unsupervised continual learning (UCL) of image representation has garnered attention due to practical need. However, recent UCL methods focus on mitigating the catastrophic forgetting with a replay buffer (i.e., rehearsal-based strategy), which needs much extra storage. To overcome this drawback, we…
Multi-agent exploration of a bounded 3D environment with the unknown initial poses of agents is a challenging problem. It requires both quickly exploring the environments and robustly merging the sub-maps built by the agents. Most existing exploration strategies directly merge two sub-maps built by
LiDAR-based localization approach is a fundamental module for large-scale navigation tasks, such as last-mile delivery and autonomous driving, and localization robustness highly relies on viewpoints and 3D feature extraction. Our previous work provides a viewpoint-invariant descriptor to deal with v