1 citations · 1 across the 4 of their papers we have counts for
8 papers
A DeepSeek-Powered AI System for Automated Chest Radiograph Interpretation in Clinical Practice
Yaowei Bai, Ruiheng Zhang, Yu Lei +20
A global shortage of radiologists has been exacerbated by the significant volume of chest X-ray workloads, particularly in primary care. Although multimodal large language models s…
Rethink Sparse Signals for Pose-guided Text-to-image Generation
Wenjie Xuan, Jing Zhang, Juhua Liu +2
Recent works favored dense signals (e.g., depth, DensePose), as an alternative to sparse signals (e.g., OpenPose), to provide detailed spatial guidance for pose-guided text-to-imag…
Resolving Knowledge Conflicts in Domain-specific Data Selection: A Case Study on Medical Instruction-tuning
Qihuang Zhong, Liang Ding, Fei Liao +3
Domain-specific instruction-tuning has become the defacto standard for improving the performance of large language models (LLMs) in specialized applications, e.g., medical question…
Advances in Radiance Field for Dynamic Scene: From Neural Field to Gaussian Field
Jinlong Fan, Xuepu Zeng, Jing Zhang +3
Dynamic scene representation and reconstruction have undergone transformative advances in recent years, catalyzed by breakthroughs in neural radiance fields and 3D Gaussian splatti…
Reasoning-OCR: Can Large Multimodal Models Solve Complex Logical Reasoning Problems from OCR Cues?
Haibin He, Maoyuan Ye, Jing Zhang +4
Large Multimodal Models (LMMs) have become increasingly versatile, accompanied by impressive Optical Character Recognition (OCR) related capabilities. Existing OCR-related benchmar…
GoMatching++: Parameter- and Data-Efficient Arbitrary-Shaped Video Text Spotting and Benchmarking
Haibin He, Jing Zhang, Maoyuan Ye +3
Video text spotting (VTS) extends image text spotting (ITS) by adding text tracking, significantly increasing task complexity. Despite progress in VTS, existing methods still fall…