2 citations · 2 across the 6 of their papers we have counts for
6 papers
VoCap: Video Object Captioning and Segmentation from Any Prompt
Jasper Uijlings, Xingyi Zhou, Xiuye Gu +5
Understanding objects in videos in terms of fine-grained localization masks and detailed semantic properties is a fundamental task in video understanding. In this paper, we propose…
Neptune: The Long Orbit to Benchmarking Long Video Understanding
Arsha Nagrani, Mingda Zhang, Ramin Mehran +10
We introduce Neptune, a benchmark for long video understanding that requires reasoning over long time horizons and across different modalities. Many existing video datasets and mod…
Visual Lexicon: Rich Image Features in Language Space
XuDong Wang, Xingyi Zhou, Alireza Fathi +2
We present Visual Lexicon, a novel visual language that encodes rich image information into the text space of vocabulary tokens while retaining intricate visual details that are of…
Streaming Dense Video Captioning
Xingyi Zhou, Anurag Arnab, Shyamal Buch +5
An ideal model for dense video captioning -- predicting captions localized temporally in a video -- should be able to handle long input videos, predict rich, detailed textual descr…
Distilling Vision-Language Models on Millions of Videos
Yue Zhao, Long Zhao, Xingyi Zhou +9
The recent advance in vision-language models is largely attributed to the abundance of image-text data. We aim to replicate this success for video-language models, but there simply…
Pixel Aligned Language Models
Jiarui Xu, Xingyi Zhou, Shen Yan +5
Large language models have achieved great success in recent years, so as their variants in vision. Existing vision-language models can describe images in natural languages, answer…