84 citations · 93 across the 8 of their papers we have counts for
8 papers
Accommodating Audio Modality in CLIP for Multimodal Processing
Ludan Ruan, Anwen Hu, Yuqing Song +3
Multimodal processing has attracted much attention lately especially with the success of pre-training. However, the exploration has mainly focused on vision-language pre-training,…
Unifying Event Detection and Captioning as Sequence Generation via Pre-Training
Qi Zhang, Yuqing Song, Qin Jin
Dense video captioning aims to generate corresponding text descriptions for a series of events in the untrimmed video, which can be divided into two sub-tasks, event detection and…
Product-oriented Machine Translation with Cross-modal Cross-lingual Pre-training
Yuqing Song, Shizhe Chen, Qin Jin +3
Translating e-commercial product descriptions, a.k.a product-oriented machine translation (PMT), is essential to serve e-shoppers all over the world. However, due to the domain spe…
Team RUC_AIM3 Technical Report at ActivityNet 2021: Entities Object Localization
Ludan Ruan, Jieting Chen, Yuqing Song +2
Entities Object Localization (EOL) aims to evaluate how grounded or faithful a description is, which consists of caption generation and object grounding. Previous works tackle this…
Towards Diverse Paragraph Captioning for Untrimmed Videos
Yuqing Song, Shizhe Chen, Qin Jin
Video paragraph captioning aims to describe multiple events in untrimmed videos with descriptive paragraphs. Existing approaches mainly solve the problem in two steps: event detect…
WenLan: Bridging Vision and Language by Large-Scale Multi-Modal Pre-Training
Yuqi Huo, Manli Zhang, Guangzhen Liu +32
Multi-modal pre-training models have been intensively explored to bridge vision and language in recent years. However, most of them explicitly model the cross-modal interaction bet…
Team RUC_AIM3 Technical Report at Activitynet 2020 Task 2: Exploring Sequential Events Detection for Dense Video Captioning
Yuqing Song, Shizhe Chen, Yida Zhao +1
Detecting meaningful events in an untrimmed video is essential for dense video captioning. In this work, we propose a novel and simple model for event sequence generation and explo…
RUC+CMU: System Report for Dense Captioning Events in Videos
Shizhe Chen, Yuqing Song, Yida Zhao +3
This notebook paper presents our system in the ActivityNet Dense Captioning in Video task (task 3). Temporal proposal generation and caption generation are both important to the de…