activity
20192022
most citedDMC-Net: Generating Discriminative Motion Cues for Fast Compressed Video Action Recognition

10 citations · 43 across the 9 of their papers we have counts for

collaborators

11 papers

cs.CV20222 cited

Video Event Extraction via Tracking Visual States of Arguments

Guang Yang, Manling Li, Jiajie Zhang +3

Video event extraction aims to detect salient events from a video and identify the arguments for each event as well as their semantic roles. Existing methods focus on capturing the…

cs.CV20228 cited

Learning to Decompose Visual Features with Latent Textual Prompts

Feng Wang, Manling Li, Xudong Lin +3

Recent advances in pre-training vision-language models like CLIP have shown great potential in learning transferable visual representations. Nonetheless, for downstream inference,…

cs.CV20223 cited

All in One: Exploring Unified Video-Language Pre-training

Alex Jinpeng Wang, Yixiao Ge, Rui Yan +7

Mainstream Video-Language Pre-training models \cite{actbert,clipbert,violet} consist of three parts, a video encoder, a text encoder, and a video-text fusion Transformer. They purs…

cs.CV20213 cited

Joint Multimedia Event Extraction from Video and Article

Brian Chen, Xudong Lin, Christopher Thomas +5

Visual and textual modalities contribute complementary information about events described in multimedia documents. Videos contain rich dynamics and detailed unfoldings of events, w…

cs.CV20211 cited

Co-Grounding Networks with Semantic Attention for Referring Expression Comprehension in Videos

Sijie Song, Xudong Lin, Jiaying Liu +2

In this paper, we address the problem of referring expression comprehension in videos, which is challenging due to complex expression and scene dynamics. Unlike previous methods wh…

cs.CV20218 cited

VX2TEXT: End-to-End Learning of Video-Based Text Generation From Multimodal Inputs

Xudong Lin, Gedas Bertasius, Jue Wang +3

We present \textsc{Vx2Text}, a framework for text generation from multimodal inputs consisting of video plus text, speech, or audio. In order to leverage transformer networks, whic…