5 papers
Bridging Fidelity-Reality with Controllable One-Step Diffusion for Image Super-Resolution
Hao Chen, Junyang Chen, Jinshan Pan +1
Recent diffusion-based one-step methods have shown remarkable progress in the field of image super-resolution, yet they remain constrained by three critical limitations: (1) inferi…
FBAD: Frequency-based Black-box Attack for AI-generated Image Detection
Xiaojing Chen, Dan Li, Lijun Peng +6
The prosperous development of Artificial Intelligence-Generated Content (AIGC) has brought people's anxiety about the spread of false information on social media. Designing detecto…
STCDiT: Spatio-Temporally Consistent Diffusion Transformer for High-Quality Video Super-Resolution
Junyang Chen, Jiangxin Dong, Long Sun +2
We present STCDiT, a video super-resolution framework built upon a pre-trained video diffusion model, aiming to restore structurally faithful and temporally stable videos from degr…
Pretrain like Your Inference: Masked Tuning Improves Zero-Shot Composed Image Retrieval
Junyang Chen, Hanjiang Lai
Zero-shot composed image retrieval (ZS-CIR), which takes a textual modification and a reference image as a query to retrieve a target image without triplet labeling, has gained mor…
FaithDiff: Unleashing Diffusion Priors for Faithful Image Super-resolution
Junyang Chen, Jinshan Pan, Jiangxin Dong
Faithful image super-resolution (SR) not only needs to recover images that appear realistic, similar to image generation tasks, but also requires that the restored images maintain…