7 papers
SafeGuard: A Multi-Agent Perception-Reasoning Framework for Social-Risk AI-Generated Video Detection
Wenlin Wu, Sheng Zhou, Peipei Song +3
As video generation paradigms evolve from localized manipulation to full-scene synthesis, AI-generated video detection becomes increasingly challenging, as forgeries exhibit cohere…
Enhancing Partially Relevant Video Retrieval with Robust Alignment Learning
Long Zhang, Peipei Song, Jianfeng Dong +2
Partially Relevant Video Retrieval (PRVR) aims to retrieve untrimmed videos partially relevant to a given query. The core challenge lies in learning robust query-video alignment ag…
Towards Efficient Partially Relevant Video Retrieval with Active Moment Discovering
Peipei Song, Long Zhang, Long Lan +4
Partially relevant video retrieval (PRVR) is a practical yet challenging task in text-to-video retrieval, where videos are untrimmed and contain much background content. The pursui…
Linguistics-Vision Monotonic Consistent Network for Sign Language Production
Xu Wang, Shengeng Tang, Peipei Song +3
Sign Language Production (SLP) aims to generate sign videos corresponding to spoken language sentences, where the conversion of sign Glosses to Poses (G2P) is the key step. Due to…
PEMF-VTO: Point-Enhanced Video Virtual Try-on via Mask-free Paradigm
Tianyu Chang, Xiaohao Chen, Zhichao Wei +5
Video Virtual Try-on aims to seamlessly transfer a reference garment onto a target person in a video while preserving both visual fidelity and temporal coherence. Existing methods…
Scene-Text Grounding for Text-Based Video Question Answering
Sheng Zhou, Junbin Xiao, Xun Yang +5
Existing efforts in text-based video question answering (TextVideoQA) are criticized for their opaque decisionmaking and heavy reliance on scene-text recognition. In this paper, we…
Recurrent Relational Memory Network for Unsupervised Image Captioning
Dan Guo, Yang Wang, Peipei Song +1
Unsupervised image captioning with no annotations is an emerging challenge in computer vision, where the existing arts usually adopt GAN (Generative Adversarial Networks) models. I…