5 papers · 1 filter
What Makes LVLMs Hallucinate Less? Unveiling the Architectural Factors Behind Hallucination Robustness
Yusheng He, Jizhe Zhou, Xia Du +3
Hallucination remains one of the key challenges undermining the reliability of Large Vision-Language Models (LVLMs). But what makes an LVLM hallucinate less? Many existing efforts…
Beyond Visual Appearances: Privacy-sensitive Objects Identification via Hybrid Graph Reasoning
Zhuohang Jiang, Bingkui Tong, Xia Du +2
The Privacy-sensitive Object Identification (POI) task allocates bounding boxes for privacy-sensitive objects in a scene. The key to POI is settling an object's privacy class (priv…
SHAN: Object-Level Privacy Detection via Inference on Scene Heterogeneous Graph
Zhuohang Jiang, Bingkui Tong, Xia Du +2
With the rise of social platforms, protecting privacy has become an important issue. Privacy object detection aims to accurately locate private objects in images. It is the foundat…
Pre-training-free Image Manipulation Localization through Non-Mutually Exclusive Contrastive Learning
Jizhe Zhou, Xiaochen Ma, Xia Du +2
Deep Image Manipulation Localization (IML) models suffer from training data insufficiency and thus heavily rely on pre-training. We argue that contrastive learning is more suitable…
IML-ViT: Benchmarking Image Manipulation Localization by Vision Transformer
Xiaochen Ma, Bo Du, Zhuohang Jiang +3
Advanced image tampering techniques are increasingly challenging the trustworthiness of multimedia, leading to the development of Image Manipulation Localization (IML). But what ma…