5 papers · 1 filter
FOCUS: Frequency-Optimized Conditioning of DiffUSion Models for mitigating catastrophic forgetting during Test-Time Adaptation
Gabriel Tjio, Jie Zhang, Xulei Yang +6
Test-time adaptation enables models to adapt to evolving domains. However, balancing the tradeoff between preserving knowledge and adapting to domain shifts remains challenging for…
Time-variant Image Inpainting via Interactive Distribution Transition Estimation
Yun Xing, Qing Guo, Xiaoguang Li +5
In this work, we focus on a novel and practical task, i.e., Time-vAriant iMage inPainting (TAMP). The aim of TAMP is to restore a damaged target image by leveraging the complementa…
Trust-Aware Diversion for Data-Effective Distillation
Zhuojie Wu, Yanbin Liu, Xin Shen +2
Dataset distillation compresses a large dataset into a small synthetic subset that retains essential information. Existing methods assume that all samples are perfectly labeled, li…
EmoAttack: Emotion-to-Image Diffusion Models for Emotional Backdoor Generation
Tianyu Wei, Shanmin Pang, Qi Guo +3
Text-to-image diffusion models can generate realistic images based on textual inputs, enabling users to convey their opinions visually through language. Meanwhile, within language,…
IRAD: Implicit Representation-driven Image Resampling against Adversarial Attacks
Yue Cao, Tianlin Li, Xiaofeng Cao +3
We introduce a novel approach to counter adversarial attacks, namely, image resampling. Image resampling transforms a discrete image into a new one, simulating the process of scene…