activity
20192021
most citedLearning to Anticipate Egocentric Actions by Imagination

64 citations · 109 across the 8 of their papers we have counts for

collaborators

10 papers

cs.CV20211 cited

Contrastive Video-Language Segmentation

Chen Liang, Yawei Luo, Yu Wu +1

We focus on the problem of segmenting a certain object referred by a natural language sentence in video content, at the core of formulating a pinpoint vision-language relation. Whi…

cs.CV2021

Saying the Unseen: Video Descriptions via Dialog Agents

Ye Zhu, Yu Wu, Yi Yang +1

Current vision and language tasks usually take complete visual data (e.g., raw images or videos) as input, however, practical scenarios may often consist the situations where part…

cs.CV20211 cited

Learning Audio-Visual Correlations from Variational Cross-Modal Generation

Ye Zhu, Yu Wu, Hugo Latapie +2

People can easily imagine the potential sound while seeing an event. This natural synchronization between audio and visual signals reveals their intrinsic correlations. To this end…

cs.CV202164 cited

Learning to Anticipate Egocentric Actions by Imagination

Yu Wu, Linchao Zhu, Xiaohan Wang +2

Anticipating actions before they are executed is crucial for a wide range of practical applications, including autonomous driving and robotics. In this paper, we study the egocentr…

cs.CV2020

Describing Unseen Videos via Multi-Modal Cooperative Dialog Agents

Ye Zhu, Yu Wu, Yi Yang +1

With the arising concerns for the AI systems provided with direct access to abundant sensitive information, researchers seek to develop more reliable AI with implicit information s…

cs.CV202022 cited

Unsupervised Person Re-identification via Softened Similarity Learning

Yutian Lin, Lingxi Xie, Yu Wu +2

Person re-identification (re-ID) is an important topic in computer vision. This paper studies the unsupervised setting of re-ID, which does not require any labeled information and…