45 citations · 79 across the 10 of their papers we have counts for
10 papers
Baton: Explicit Semantic Blueprints for Joint Video-Audio Generation
Shuyuan Tu, Qi Tian, Zihan Yang +9
Current open-source diffusion models struggle to generate stable and synchronized audio-visual content, particularly in scenarios demanding complex semantic reasoning. The root cau…
Global and Local Semantic Completion Learning for Vision-Language Pre-training
Rong-Cheng Tu, Yatai Ji, Jie Jiang +6
Cross-modal alignment plays a crucial role in vision-language pre-training (VLP) models, enabling them to capture meaningful associations across different modalities. For this purp…
Seeing What You Miss: Vision-Language Pre-training with Semantic Completion Learning
Yatai Ji, Rongcheng Tu, Jie Jiang +6
Cross-modal alignment is essential for vision-language pre-training (VLP) models to learn the correct corresponding information across different modalities. For this purpose, inspi…
Egocentric Video-Language Pretraining @ Ego4D Challenge 2022
Kevin Qinghong Lin, Alex Jinpeng Wang, Mattia Soldan +13
In this report, we propose a video-language pretraining (VLP) based solution \cite{kevin2022egovlp} for four Ego4D challenge tasks, including Natural Language Query (NLQ), Moment Q…
Egocentric Video-Language Pretraining @ EPIC-KITCHENS-100 Multi-Instance Retrieval Challenge 2022
Kevin Qinghong Lin, Alex Jinpeng Wang, Rui Yan +9
In this report, we propose a video-language pretraining (VLP) based solution \cite{kevin2022egovlp} for the EPIC-KITCHENS-100 Multi-Instance Retrieval (MIR) challenge. Especially,…
Egocentric Video-Language Pretraining
Kevin Qinghong Lin, Alex Jinpeng Wang, Mattia Soldan +13
Video-Language Pretraining (VLP), which aims to learn transferable representation to advance a wide range of video-text downstream tasks, has recently received increasing attention…
Tencent Text-Video Retrieval: Hierarchical Cross-Modal Interactions with Multi-Level Representations
Jie Jiang, Shaobo Min, Weijie Kong +4
Text-Video Retrieval plays an important role in multi-modal understanding and has attracted increasing attention in recent years. Most existing methods focus on constructing contra…
Graph Convolutional Label Noise Cleaner: Train a Plug-and-play Action Classifier for Anomaly Detection
Jia-Xing Zhong, Nannan Li, Weijie Kong +3
Video anomaly detection under weak labels is formulated as a typical multiple-instance learning problem in previous works. In this paper, we provide a new perspective, i.e., a supe…
BLP -- Boundary Likelihood Pinpointing Networks for Accurate Temporal Action Localization
Weijie Kong, Nannan Li, Shan Liu +2
Despite tremendous progress achieved in temporal action detection, state-of-the-art methods still suffer from the sharp performance deterioration when localizing the starting and e…
Step-by-step Erasion, One-by-one Collection: A Weakly Supervised Temporal Action Detector
Jia-Xing Zhong, Nannan Li, Weijie Kong +3
Weakly supervised temporal action detection is a Herculean task in understanding untrimmed videos, since no supervisory signal except the video-level category label is available on…