activity
20182024
most citedRTQ: Rethinking Video-language Understanding Based on Image-text Model

14 citations · 50 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2024★ 4 cited

SNP-S3: Shared Network Pre-training and Significant Semantic Strengthening for Various Video-Text Tasks

Xingning Dong, Qingpei Guo, Tian Gan +5

We present a framework for learning cross-modal video representations by directly pre-training on raw data to facilitate various downstream video-text tasks. Our main contributions…

cs.CV2023★ 14 cited

RTQ: Rethinking Video-language Understanding Based on Image-text Model

Xiao Wang, Yaoyu Li, Tian Gan +3

Recent advancements in video-language understanding have been established on the foundation of image-text models, resulting in promising outcomes due to the shared knowledge betwee…

cs.CV2023★ 5 cited

Temporal Sentence Grounding in Streaming Videos

Tian Gan, Xiao Wang, Yan Sun +3

This paper aims to tackle a novel task - Temporal Sentence Grounding in Streaming Videos (TSGSV). The goal of TSGSV is to evaluate the relevance between a video stream and a given…

cs.MM2023★ 8 cited

Micro-video Tagging via Jointly Modeling Social Influence and Tag Relation

Xiao Wang, Tian Gan, Yinwei Wei +3

The last decade has witnessed the proliferation of micro-videos on various user-generated content platforms. According to our statistics, around 85.7\% of micro-videos lack annotat…

cs.CV2022★ 6 cited

Stacked Hybrid-Attention and Group Collaborative Learning for Unbiased Scene Graph Generation

Xingning Dong, Tian Gan, Xuemeng Song +3

Scene Graph Generation, which generally follows a regular encoder-decoder pipeline, aims to first encode the visual contents within the given image and then parse them into a compa…

cs.CL2018★ 13 cited

Explicit Interaction Model towards Text Classification

Cunxiao Du, Zhaozheng Chin, Fuli Feng +3

Text classification is one of the fundamental tasks in natural language processing. Recently, deep neural networks have achieved promising performance in the text classification ta…