6 accepted papers
Vision-and-Language Navigation in Continuous Environments (VLN-CE) requires agents to navigate 3D environments based on visual observations and natural language instructions. Existing approaches, focused on topological and semantic maps, often face limitations in accurately understanding and adaptin
Reducing radiation doses benefits patients, but the resultant low-dose computed tomography (LDCT) images often suffer from clinically unacceptable noise and artifacts. While deep learning (DL) has shown promise in LDCT reconstruction, it requires large-scale data collection from multiple clients, ra…
In the fast-evolving field of medical image analysis, deep Learning (DL)-based methods have achieved tremendous success. However, these methods require plaintext data for training and inference stages, raising privacy concerns, especially in the sensitive area of medical data. To tackle these concer…
Text-based Person Search is one of the downstream tasks of cross-modal retrieval. The key challenge is aligning features of two extremely irrelavant modalities into the same latent space. Recent works within Prototype Learning introduce a few learnable parameters to map heterogeneous features into t…
Most existing transformer-based trackers use ViT [1] as the backbone to extract and fuse feature tokens of target templates and search region. Since both the target template and the search region contain background information, their tokens are prone to background interference in interaction that af…
Most deep trackers still follow the guidance of the siamese paradigms and use a template that contains only the target without any contextual information, which makes it difficult for the tracker to cope with large appearance changes, rapid target movement, and attraction from similar objects. To al…