most citedmPLUG-2: A Modularized Multi-modal Foundation Model Across Text, Image and Video

50 citations · 95 across the 11 of their papers we have counts for

collaborators

11 papers

cs.CL2024

MaVEn: An Effective Multi-granularity Hybrid Visual Encoding Framework for Multimodal Large Language Model

Chaoya Jiang, Jia Hongrui, Haiyang Xu +6

This paper presents MaVEn, an innovative Multi-granularity Visual Encoding framework designed to enhance the capabilities of Multimodal Large Language Models (MLLMs) in multi-image…

cs.CV20246 cited

mPLUG-Owl3: Towards Long Image-Sequence Understanding in Multi-Modal Large Language Models

Jiabo Ye, Haiyang Xu, Haowei Liu +6

Multi-modal Large Language Models (MLLMs) have demonstrated remarkable capabilities in executing instructions for a variety of single-image tasks. Despite this progress, significan…

cs.CV2024

OmniControlNet: Dual-stage Integration for Conditional Image Generation

Yilin Wang, Haiyang Xu, Xiang Zhang +4

We provide a two-way integration for the widely adopted ControlNet by integrating external condition generation algorithms into a single dense prediction method and incorporating i…

cs.CV2024

Bayesian Diffusion Models for 3D Shape Reconstruction

Haiyang Xu, Yu Lei, Zeyuan Chen +4

We present Bayesian Diffusion Models (BDM), a prediction algorithm that performs effective Bayesian inference by tightly coupling the top-down (prior) information with the bottom-u…

cs.CV2024

Semantics-enhanced Cross-modal Masked Image Modeling for Vision-Language Pre-training

Haowei Liu, Yaya Shi, Haiyang Xu +8

In vision-language pre-training (VLP), masked image modeling (MIM) has recently been introduced for fine-grained cross-modal alignment. However, in most existing methods, the recon…

cs.CV20235 cited

UReader: Universal OCR-free Visually-situated Language Understanding with Multimodal Large Language Model

Jiabo Ye, Anwen Hu, Haiyang Xu +11

Text is ubiquitous in our visual world, conveying crucial information, such as in documents, websites, and everyday photographs. In this work, we propose UReader, a first explorati…