189 citations · 388 across the 31 of their papers we have counts for
4 papers · 1 filter
NÜWA: Visual Synthesis Pre-training for Neural visUal World creAtion
Chenfei Wu, Jian Liang, Lei Ji +4
This paper presents a unified multimodal pre-trained model called NÜWA that can generate new or manipulate existing visual data (i.e., images and videos) for various visual synthes…
KD-VLP: Improving End-to-End Vision-and-Language Pretraining with Object Knowledge Distillation
Yongfei Liu, Chenfei Wu, Shao-yen Tseng +3
Self-supervised vision-and-language pretraining (VLP) aims to learn transferable multi-modal representations from large-scale image-text data and to achieve strong performances on…
GEM: A General Evaluation Benchmark for Multimodal Tasks
Lin Su, Nan Duan, Edward Cui +7
In this paper, we present GEM as a General Evaluation benchmark for Multimodal tasks. Different from existing datasets such as GLUE, SuperGLUE, XGLUE and XTREME that mainly focus o…
GODIVA: Generating Open-DomaIn Videos from nAtural Descriptions
Chenfei Wu, Lun Huang, Qianxi Zhang +5
Generating videos from text is a challenging task due to its high computational requirements for training and infinite possible answers for evaluation. Existing works typically exp…