37 citations · 81 across the 14 of their papers we have counts for
14 papers
Bridging Semantic Logic Gaps: A Cognition Inspired Multimodal Boundary Preserving Network for Image Manipulation Localization
Songlin Li, Zhiqing Guo, Yuanman Li +4
The existing image manipulation localization (IML) models mainly relies on visual cues, but ignores the semantic logical relationships between content features. In fact, the conten…
Deferred Poisoning: Making the Model More Vulnerable via Hessian Singularization
Yuhao He, Jinyu Tian, Xianwei Zheng +3
Recent studies have shown that deep learning models are very vulnerable to poisoning attacks. Many defense methods have been proposed to address this issue. However, traditional po…
Image Copy-Move Forgery Detection via Deep PatchMatch and Pairwise Ranking Learning
Yuanman Li, Yingjie He, Changsheng Chen +4
Recent advances in deep learning algorithms have shown impressive progress in image copy-move forgery detection (CMFD). However, these algorithms lack generalizability in practical…
Text-Driven Traffic Anomaly Detection with Temporal High-Frequency Modeling in Driving Videos
Rongqin Liang, Yuanman Li, Jiantao Zhou +1
Traffic anomaly detection (TAD) in driving videos is critical for ensuring the safety of autonomous driving and advanced driver assistance systems. Previous single-stage TAD method…
Multi-scale Target-Aware Framework for Constrained Image Splicing Detection and Localization
Yuxuan Tan, Yuanman Li, Limin Zeng +3
Constrained image splicing detection and localization (CISDL) is a fundamental task of multimedia forensics, which detects splicing operation between two suspected images and local…
Image Copy-Move Forgery Detection via Deep Cross-Scale PatchMatch
Yingjie He, Yuanman Li, Changsheng Chen +1
The recently developed deep algorithms achieve promising progress in the field of image copy-move forgery detection (CMFD). However, they have limited generalizability in some prac…
Rethinking Image Forgery Detection via Soft Contrastive Learning and Unsupervised Clustering
Haiwei Wu, Yiming Chen, Jiantao Zhou +1
Image forgery detection aims to detect and locate forged regions in an image. Most existing forgery detection algorithms formulate classification problems to classify pixels into f…
A Memory-Augmented Multi-Task Collaborative Framework for Unsupervised Traffic Accident Detection in Driving Videos
Rongqin Liang, Yuanman Li, Yingxin Yi +2
Identifying traffic accidents in driving videos is crucial to ensuring the safety of autonomous driving and driver assistance systems. To address the potential danger caused by the…
STGlow: A Flow-based Generative Framework with Dual Graphormer for Pedestrian Trajectory Prediction
Rongqin Liang, Yuanman Li, Jiantao Zhou +1
The pedestrian trajectory prediction task is an essential component of intelligent systems. Its applications include but are not limited to autonomous driving, robot navigation, an…
Uformer-ICS: A U-Shaped Transformer for Image Compressive Sensing Service
Kuiyuan Zhang, Zhongyun Hua, Yuanman Li +2
Many service computing applications require real-time dataset collection from multiple devices, necessitating efficient sampling techniques to reduce bandwidth and storage pressure…
Video Salient Object Detection via Adaptive Local-Global Refinement
Yi Tang, Yuanman Li, Guoliang Xing
Video salient object detection (VSOD) is an important task in many vision applications. Reliable VSOD requires to simultaneously exploit the information from both the spatial domai…
Detecting Adversarial Examples from Sensitivity Inconsistency of Spatial-Transform Domain
Jinyu Tian, Jiantao Zhou, Yuanman Li +1
Deep neural networks (DNNs) have been shown to be vulnerable against adversarial examples (AEs), which are maliciously designed to cause dramatic model output errors. In this work,…
Temporal Pyramid Network for Pedestrian Trajectory Prediction with Multi-Supervision
Rongqin Liang, Yuanman Li, Xia Li +3
Predicting human motion behavior in a crowd is important for many applications, ranging from the natural navigation of autonomous vehicles to intelligent security systems of video…
Deep Generative Model for Image Inpainting with Local Binary Pattern Learning and Spatial Attention
Haiwei Wu, Jiantao Zhou, Yuanman Li
Deep learning (DL) has demonstrated its powerful capabilities in the field of image inpainting. The DL-based image inpainting approaches can produce visually plausible results, but…