4 citations · 8 across the 13 of their papers we have counts for
13 papers
PHASOR: Anatomy- and Phase-Consistent Volumetric Diffusion for CT Virtual Contrast Enhancement
Zilong Li, Dongyang Li, Chenglong Ma +6
Contrast-enhanced computed tomography (CECT) is pivotal for highlighting tissue perfusion and vascularity, yet its clinical ubiquity is impeded by the invasive nature of contrast a…
MieDB-100k: A Comprehensive Dataset for Medical Image Editing
Yongfan Lai, Wen Qian, Bo Liu +5
The scarcity of high-quality data remains a primary bottleneck in adapting multimodal generative models for medical image editing. Existing medical image editing datasets often suf…
MedGround: Bridging the Evidence Gap in Medical Vision-Language Models with Verified Grounding Data
Mengmeng Zhang, Xiaoping Wu, Hao Luo +2
Vision-Language Models (VLMs) can generate convincing clinical narratives, yet frequently struggle to visually ground their statements. We posit that this limitation arises from th…
Preacher: Paper-to-Video Agentic System
Jingwei Liu, Ling Yang, Hao Luo +3
The paper-to-video task converts a research paper into a structured video abstract, distilling key concepts, methods, and conclusions into an accessible, well-organized format. Whi…
DyDiT++: Diffusion Transformers with Timestep and Spatial Dynamics for Efficient Visual Generation
Wangbo Zhao, Yizeng Han, Jiasheng Tang +6
Diffusion Transformer (DiT), an emerging diffusion model for visual generation, has demonstrated superior performance but suffers from substantial computational costs. Our investig…
AnyLogo: Symbiotic Subject-Driven Diffusion System with Gemini Status
Jinghao Zhang, Wen Qian, Hao Luo +2
Diffusion models have made compelling progress on facilitating high-throughput daily production. Nevertheless, the appealing customized requirements are remain suffered from instan…
Uncovering the Text Embedding in Text-to-Image Diffusion Models
Hu Yu, Hao Luo, Fan Wang +1
The correspondence between input text and the generated image exhibits opacity, wherein minor textual modifications can induce substantial deviations in the generated image. While,…
Text Data-Centric Image Captioning with Interactive Prompts
Yiyu Wang, Hao Luo, Jungang Xu +2
Supervised image captioning approaches have made great progress, but it is challenging to collect high-quality human-annotated image-text data. Recently, large-scale vision and lan…
Accelerating Parallel Sampling of Diffusion Models
Zhiwei Tang, Jiasheng Tang, Hao Luo +2
Diffusion models have emerged as state-of-the-art generative models for image generation. However, sampling from diffusion models is usually time-consuming due to the inherent auto…
CL2CM: Improving Cross-Lingual Cross-Modal Retrieval via Cross-Lingual Knowledge Transfer
Yabing Wang, Fan Wang, Jianfeng Dong +1
Cross-lingual cross-modal retrieval has garnered increasing attention recently, which aims to achieve the alignment between vision and target language (V-T) without using any annot…
Dual-view Curricular Optimal Transport for Cross-lingual Cross-modal Retrieval
Yabing Wang, Shuhui Wang, Hao Luo +5
Current research on cross-modal retrieval is mostly English-oriented, as the availability of a large number of English-oriented human-labeled vision-language corpora. In order to b…
SCT: A Simple Baseline for Parameter-Efficient Fine-Tuning via Salient Channels
Henry Hengyuan Zhao, Pichao Wang, Yuyang Zhao +3
Pre-trained vision transformers have strong representation benefits to various downstream tasks. Recently, many parameter-efficient fine-tuning (PEFT) methods have been proposed, a…
DiffAug: Enhance Unsupervised Contrastive Learning with Domain-Knowledge-Free Diffusion-based Data Augmentation
Zelin Zang, Hao Luo, Kai Wang +4
Unsupervised Contrastive learning has gained prominence in fields such as vision, and biology, leveraging predefined positive/negative samples for representation learning. Data aug…