most citedDVG-Diffusion: Dual-View Guided Diffusion Model for CT Reconstruction from X-Rays

1 citations · 1 across the 4 of their papers we have counts for

collaborators

10 papers

cs.CV2025

Discrete Diffusion Models with MLLMs for Unified Medical Multimodal Generation

Jiawei Mao, Yuhan Wang, Lifeng Chen +6

Recent advances in generative medical models are constrained by modality-specific scenarios that hinder the integration of complementary evidence from imaging, pathology, and clini…

cs.CV2025

DSKC: Domain Style Modeling with Adaptive Knowledge Consolidation for Exemplar-free Lifelong Person Re-Identification

Shiben Liu, Mingyue Xu, Huijie Fan +3

Lifelong Person Re-identification (LReID) aims to continuously match individuals across camera views from sequential data streams. Existing LReID methods often ignore domain-specif…

cs.CV2025

ATSTrack: Enhancing Visual-Language Tracking by Aligning Temporal and Spatial Scales

Yihao Zhen, Qiang Wang, Yu Qiao +2

A main challenge of Visual-Language Tracking (VLT) is the misalignment between visual inputs and language descriptions caused by target movement. Previous trackers have explored ma…

cs.LG2025

FedVLMBench: Benchmarking Federated Fine-Tuning of Vision-Language Models

Weiying Zheng, Ziyue Lin, Pengxin Guo +3

Vision-Language Models (VLMs) have demonstrated remarkable capabilities in cross-modal understanding and generation by integrating visual and textual information. While instruction…

cs.CV2025

Distribution-aware Forgetting Compensation for Exemplar-Free Lifelong Person Re-identification

Shiben Liu, Huijie Fan, Qiang Wang +3

Lifelong Person Re-identification (LReID) suffers from a key challenge in preserving old knowledge while adapting to new information. The existing solutions include rehearsal-based…

eess.IV20251 cited

DVG-Diffusion: Dual-View Guided Diffusion Model for CT Reconstruction from X-Rays

Xing Xie, Jiawei Liu, Huijie Fan +3

Directly reconstructing 3D CT volume from few-view 2D X-rays using an end-to-end deep learning network is a challenging task, as X-ray images are merely projection views of the 3D…