9 papers
CFCML: A Coarse-to-Fine Crossmodal Learning Framework For Disease Diagnosis Using Multimodal Images and Tabular Data
Tianling Liu, Hongying Liu, Fanhua Shang +3
In clinical practice, crossmodal information including medical images and tabular data is essential for disease diagnosis. There exists a significant modality gap between these dat…
PDD: Manifold-Prior Diverse Distillation for Medical Anomaly Detection
Xijun Lu, Hongying Liu, Fanhua Shang +2
Medical image anomaly detection faces unique challenges due to subtle, heterogeneous anomalies embedded in complex anatomical structures. Through systematic Grad-CAM analysis, we r…
SSL-SSAW: Self-Supervised Learning with Sigmoid Self-Attention Weighting for Question-Based Sign Language Translation
Zekang Liu, Wei Feng, Fanhua Shang +3
Sign Language Translation (SLT) bridges the communication gap between deaf people and hearing people, where dialogue provides crucial contextual cues to aid in translation. Buildin…
LightVLM: Acceleraing Large Multimodal Models with Pyramid Token Merging and KV Cache Compression
Lianyu Hu, Fanhua Shang, Wei Feng +1
In this paper, we introduce LightVLM, a simple but effective method that can be seamlessly deployed upon existing Vision-Language Models (VLMs) to greatly accelerate the inference…
FedSWA: Improving Generalization in Federated Learning with Highly Heterogeneous Data via Momentum-Based Stochastic Controlled Weight Averaging
Liu junkang, Yuanyuan Liu, Fanhua Shang +3
For federated learning (FL) algorithms such as FedSAM, their generalization capability is crucial for real-word applications. In this paper, we revisit the generalization problem i…
Beyond Background Shift: Rethinking Instance Replay in Continual Semantic Segmentation
Hongmei Yin, Tingliang Feng, Fan Lyu +4
In this work, we focus on continual semantic segmentation (CSS), where segmentation networks are required to continuously learn new classes without erasing knowledge of previously…