80 citations · 112 across the 7 of their papers we have counts for
7 papers · 1 filter
Advancing Visual Grounding with Scene Knowledge: Benchmark and Method
Zhihong Chen, Ruifei Zhang, Yibing Song +2
Visual grounding (VG) aims to establish fine-grained alignment between vision and language. Ideally, it can be a testbed for vision-and-language models to evaluate their understand…
Bridging Vision and Language Encoders: Parameter-Efficient Tuning for Referring Image Segmentation
Zunnan Xu, Zhihong Chen, Yong Zhang +3
Parameter Efficient Tuning (PET) has gained attention for reducing the number of parameters while maintaining performance and providing better hardware resource savings, but few st…
Attentive Symmetric Autoencoder for Brain MRI Segmentation
Junjia Huang, Haofeng Li, Guanbin Li +1
Self-supervised learning methods based on image patch reconstruction have witnessed great success in training auto-encoders, whose pre-trained weights can be transferred to fine-tu…
Medical-VLBERT: Medical Visual Language BERT for COVID-19 CT Report Generation With Alternate Learning
Guangyi Liu, Yinghong Liao, Fuyu Wang +8
Medical imaging technologies, including computed tomography (CT) or chest X-Ray (CXR), are largely employed to facilitate the diagnosis of the COVID-19. Since manual report writing…
Multi-Modal Active Learning for Automatic Liver Fibrosis Diagnosis based on Ultrasound Shear Wave Elastography
Lufei Gao, Ruisong Zhou, Changfeng Dong +4
With the development of radiomics, noninvasive diagnosis like ultrasound (US) imaging plays a very important role in automatic liver fibrosis diagnosis (ALFD). Due to the noisy dat…
USCL: Pretraining Deep Ultrasound Image Diagnosis Model through Video Contrastive Representation Learning
Yixiong Chen, Chunhui Zhang, Li Liu +4
Most deep neural networks (DNNs) based ultrasound (US) medical image analysis models use pretrained backbones (e.g., ImageNet) for better model generalization. However, the domain…