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20162024
most citedREFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographs

858 citations · 2.9k across the 84 of their papers we have counts for

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87 papers · 1 filter

cs.CV2024

Cross Prompting Consistency with Segment Anything Model for Semi-supervised Medical Image Segmentation

Juzheng Miao, Cheng Chen, Keli Zhang +3

Semi-supervised learning (SSL) has achieved notable progress in medical image segmentation. To achieve effective SSL, a model needs to be able to efficiently learn from limited lab…

cs.CV2024

FM-OSD: Foundation Model-Enabled One-Shot Detection of Anatomical Landmarks

Juzheng Miao, Cheng Chen, Keli Zhang +3

One-shot detection of anatomical landmarks is gaining significant attention for its efficiency in using minimal labeled data to produce promising results. However, the success of c…

cs.CV20241 cited

Multi-scale Spatio-temporal Transformer-based Imbalanced Longitudinal Learning for Glaucoma Forecasting from Irregular Time Series Images

Xikai Yang, Jian Wu, Xi Wang +3

Glaucoma is one of the major eye diseases that leads to progressive optic nerve fiber damage and irreversible blindness, afflicting millions of individuals. Glaucoma forecast is a…

cs.CV20242 cited

SiMA-Hand: Boosting 3D Hand-Mesh Reconstruction by Single-to-Multi-View Adaptation

Yinqiao Wang, Hao Xu, Pheng-Ann Heng +1

Estimating 3D hand mesh from RGB images is a longstanding track, in which occlusion is one of the most challenging problems. Existing attempts towards this task often fail when the…

cs.CV20245 cited

SignVTCL: Multi-Modal Continuous Sign Language Recognition Enhanced by Visual-Textual Contrastive Learning

Hao Chen, Jiaze Wang, Ziyu Guo +6

Sign language recognition (SLR) plays a vital role in facilitating communication for the hearing-impaired community. SLR is a weakly supervised task where entire videos are annotat…

cs.CV2024

Memory-Efficient Prompt Tuning for Incremental Histopathology Classification

Yu Zhu, Kang Li, Lequan Yu +1

Recent studies have made remarkable progress in histopathology classification. Based on current successes, contemporary works proposed to further upgrade the model towards a more g…