773 citations · 1.5k across the 36 of their papers we have counts for
6 papers · 1 filter
ERNIE-UniX2: A Unified Cross-lingual Cross-modal Framework for Understanding and Generation
Bin Shan, Yaqian Han, Weichong Yin +5
Recent cross-lingual cross-modal works attempt to extend Vision-Language Pre-training (VLP) models to non-English inputs and achieve impressive performance. However, these models f…
ERNIE-ViLG 2.0: Improving Text-to-Image Diffusion Model with Knowledge-Enhanced Mixture-of-Denoising-Experts
Zhida Feng, Zhenyu Zhang, Xintong Yu +12
Recent progress in diffusion models has revolutionized the popular technology of text-to-image generation. While existing approaches could produce photorealistic high-resolution im…
ERNIE-ViL 2.0: Multi-view Contrastive Learning for Image-Text Pre-training
Bin Shan, Weichong Yin, Yu Sun +3
Recent Vision-Language Pre-trained (VLP) models based on dual encoder have attracted extensive attention from academia and industry due to their superior performance on various cro…
ERNIE-mmLayout: Multi-grained MultiModal Transformer for Document Understanding
Wenjin Wang, Zhengjie Huang, Bin Luo +8
Recent efforts of multimodal Transformers have improved Visually Rich Document Understanding (VrDU) tasks via incorporating visual and textual information. However, existing approa…
ERNIE-ViLG: Unified Generative Pre-training for Bidirectional Vision-Language Generation
Han Zhang, Weichong Yin, Yewei Fang +7
Conventional methods for the image-text generation tasks mainly tackle the naturally bidirectional generation tasks separately, focusing on designing task-specific frameworks to im…
ERNIE-ViL: Knowledge Enhanced Vision-Language Representations Through Scene Graph
Fei Yu, Jiji Tang, Weichong Yin +4
We propose a knowledge-enhanced approach, ERNIE-ViL, which incorporates structured knowledge obtained from scene graphs to learn joint representations of vision-language. ERNIE-ViL…