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Ziwei Niu

5 accepted papers

2026

CG-DMER: Hybrid Contrastive-Generative Framework for Disentangled Multimodal ECG Representation Learning

ICASSP 2026oral

Accurate interpretation of electrocardiogram (ECG) signals is crucial for diagnosing cardiovascular diseases. Recent multimodal approaches that integrate ECGs with accompanying clinical reports show strong potential, but they still face two main concerns from a modality perspective: (1) intra-modali…

Cited by 0SourcePDFScholar
2025

Region-aware Anchoring Mechanism for Efficient Referring Visual Grounding

ICCV 2025poster

Referring Visual Grounding (RVG) tasks revolve around utilizing vision-language interactions to incorporate object information from language expressions, thereby enabling targeted object detection or segmentation within images. Transformer-based methods have enabled effective interaction through att…

Cited by 0SourcePDFScholar
2024

IRLSG: Invariant Representation Learning for Single-Domain Generalization in Medical Image Segmentation

ICASSP 2024accepted

Single-domain generalization (SDG) can efficiently enhance model generalization while avoiding high annotation costs and privacy concerns. However, existing SDG methods are mainly based on data manipulation and meta-learning, which are not efficient enough due to the limited generalization performan…

Cited by 0SourceScholar
2023

MCKD: Mutually Collaborative Knowledge Distillation For Federated Domain Adaptation And Generalization

ICASSP 2023accepted

Conventional unsupervised domain adaptation (UDA) and domain generalization (DG) methods rely on the assumption that all source domains can be directly accessed and combined for model training. However, this centralized training strategy may violate privacy policies in many real-world applications.…

Cited by 0SourceScholar
2023

SLViT: Scale-Wise Language-Guided Vision Transformer for Referring Image Segmentation

IJCAI 2023poster

Referring image segmentation aims to segment an object out of an image via a specific language expression. The main concept is establishing global visual-linguistic relationships to locate the object and identify boundaries using details of the image. Recently, various Transformer-based techniques h…