5 papers
TriDF: Evaluating Perception, Detection, and Hallucination for Interpretable DeepFake Detection
Jian-Yu Jiang-Lin, Kang-Yang Huang, Ling Zou +11
Advances in generative modeling have made it increasingly easy to fabricate realistic portrayals of individuals, creating serious risks for security, communication, and public trus…
One Pool Is Not Enough: Multi-Cluster Memory for Practical Test-Time Adaptation
Yu-Wen Tseng, Xingyi Zheng, Ya-Chen Wu +4
Test-time adaptation (TTA) adapts pre-trained models to distribution shifts at inference using only unlabeled test data. Under the Practical TTA (PTTA) setting, where test streams…
InstructFLIP: Exploring Unified Vision-Language Model for Face Anti-spoofing
Kun-Hsiang Lin, Yu-Wen Tseng, Kang-Yang Huang +2
Face anti-spoofing (FAS) aims to construct a robust system that can withstand diverse attacks. While recent efforts have concentrated mainly on cross-domain generalization, two sig…
A DeNoising FPN With Transformer R-CNN for Tiny Object Detection
Hou-I Liu, Yu-Wen Tseng, Kai-Cheng Chang +3
Despite notable advancements in the field of computer vision, the precise detection of tiny objects continues to pose a significant challenge, largely owing to the minuscule pixel…
EmoVIT: Revolutionizing Emotion Insights with Visual Instruction Tuning
Hongxia Xie, Chu-Jun Peng, Yu-Wen Tseng +4
Visual Instruction Tuning represents a novel learning paradigm involving the fine-tuning of pre-trained language models using task-specific instructions. This paradigm shows promis…