342 citations · 1.2k across the 36 of their papers we have counts for
10 papers · 1 filter
The Overlooked Classifier in Human-Object Interaction Recognition
Ying Jin, Yinpeng Chen, Lijuan Wang +5
Human-Object Interaction (HOI) recognition is challenging due to two factors: (1) significant imbalance across classes and (2) requiring multiple labels per image. This paper shows…
Injecting Semantic Concepts into End-to-End Image Captioning
Zhiyuan Fang, Jianfeng Wang, Xiaowei Hu +5
Tremendous progress has been made in recent years in developing better image captioning models, yet most of them rely on a separate object detector to extract regional features. Re…
Florence: A New Foundation Model for Computer Vision
Lu Yuan, Dongdong Chen, Yi-Ling Chen +20
Automated visual understanding of our diverse and open world demands computer vision models to generalize well with minimal customization for specific tasks, similar to human visio…
UFO: A UniFied TransfOrmer for Vision-Language Representation Learning
Jianfeng Wang, Xiaowei Hu, Zhe Gan +5
In this paper, we propose a single UniFied transfOrmer (UFO), which is capable of processing either unimodal inputs (e.g., image or language) or multimodal inputs (e.g., the concat…
Scaling Up Vision-Language Pre-training for Image Captioning
Xiaowei Hu, Zhe Gan, Jianfeng Wang +4
In recent years, we have witnessed significant performance boost in the image captioning task based on vision-language pre-training (VLP). Scale is believed to be an important fact…
UniTAB: Unifying Text and Box Outputs for Grounded Vision-Language Modeling
Zhengyuan Yang, Zhe Gan, Jianfeng Wang +5
We propose UniTAB that Unifies Text And Box outputs for grounded vision-language (VL) modeling. Grounded VL tasks such as grounded captioning require the model to generate a text d…
An Empirical Study of Training End-to-End Vision-and-Language Transformers
Zi-Yi Dou, Yichong Xu, Zhe Gan +9
Vision-and-language (VL) pre-training has proven to be highly effective on various VL downstream tasks. While recent work has shown that fully transformer-based VL models can be mo…
Edge Prior Augmented Networks for Motion Deblurring on Naturally Blurry Images
Yuedong Chen, Junjia Huang, Jianfeng Wang +1
Motion deblurring has witnessed rapid development in recent years, and most of the recent methods address it by using deep learning techniques, with the help of different kinds of…
An Empirical Study of GPT-3 for Few-Shot Knowledge-Based VQA
Zhengyuan Yang, Zhe Gan, Jianfeng Wang +4
Knowledge-based visual question answering (VQA) involves answering questions that require external knowledge not present in the image. Existing methods first retrieve knowledge fro…
Is Object Detection Necessary for Human-Object Interaction Recognition?
Ying Jin, Yinpeng Chen, Lijuan Wang +4
This paper revisits human-object interaction (HOI) recognition at image level without using supervisions of object location and human pose. We name it detection-free HOI recognitio…