4 papers
AIFIND: Artifact-Aware Interpreting Fine-Grained Alignment for Incremental Face Forgery Detection
Hao Wang, Beichen Zhang, Yanpei Gong +5
As forgery types continue to emerge consistently, Incremental Face Forgery Detection (IFFD) has become a crucial paradigm. However, existing methods typically rely on data replay o…
Can Cross-Layer Transcoders Replace Vision Transformer Activations? An Interpretable Perspective on Vision
Gerasimos Chatzoudis, Konstantinos D. Polyzos, Zhuowei Li +4
Understanding the internal activations of Vision Transformers (ViTs) is critical for building interpretable and trustworthy models. While Sparse Autoencoders (SAEs) have been used…
Modality-Agnostic Prompt Learning for Multi-Modal Camouflaged Object Detection
Hao Wang, Jiqing Zhang, Xin Yang +4
Camouflaged Object Detection (COD) aims to segment objects that blend seamlessly into complex backgrounds, with growing interest in exploiting additional visual modalities to enhan…
FED-Bench: A Cross-Granular Benchmark for Disentangled Evaluation of Facial Expression Editing
Fengjian Xue, Xuecheng Wu, Heli Sun +8
Facial expression image editing requires fine-grained control to strictly preserve human identity and background while precisely manipulating expression. However, existing editing…