178 citations · 997 across the 30 of their papers we have counts for
31 papers
LLMScore: Unveiling the Power of Large Language Models in Text-to-Image Synthesis Evaluation
Yujie Lu, Xianjun Yang, Xiujun Li +2
Existing automatic evaluation on text-to-image synthesis can only provide an image-text matching score, without considering the object-level compositionality, which results in poor…
Self-supervised Pre-training with Hard Examples Improves Visual Representations
Chunyuan Li, Xiujun Li, Lei Zhang +3
Self-supervised pre-training (SSP) employs random image transformations to generate training data for visual representation learning. In this paper, we first present a modeling fra…
VinVL: Revisiting Visual Representations in Vision-Language Models
Pengchuan Zhang, Xiujun Li, Xiaowei Hu +5
This paper presents a detailed study of improving visual representations for vision language (VL) tasks and develops an improved object detection model to provide object-centric re…
MiniVLM: A Smaller and Faster Vision-Language Model
Jianfeng Wang, Xiaowei Hu, Pengchuan Zhang +5
Recent vision-language (VL) studies have shown remarkable progress by learning generic representations from massive image-text pairs with transformer models and then fine-tuning on…
Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks
Xiujun Li, Xi Yin, Chunyuan Li +9
Large-scale pre-training methods of learning cross-modal representations on image-text pairs are becoming popular for vision-language tasks. While existing methods simply concatena…
Optimus: Organizing Sentences via Pre-trained Modeling of a Latent Space
Chunyuan Li, Xiang Gao, Yuan Li +4
When trained effectively, the Variational Autoencoder (VAE) can be both a powerful generative model and an effective representation learning framework for natural language. In this…