7 papers
PAST: Prompt-Adaptive Sampling Termination for Efficient Diffusion Model
Renye Yan, Jikang Cheng, You Wu +4
While diffusion models have made significant progress in text-to-image tasks, they still exhibit limitations when directly optimizing downstream objectives. Although Reinforcement…
Explore or Converge? Stage-Guided Per-Step Optimization for Diffusion Models
Renye Yan, Jikang Cheng, You Wu +4
Diffusion models have strong generative capabilities. However, their maximum likelihood training objective only focuses on reconstructing the data distribution, making it difficult…
Pixel-Space Diffusion Transformers
Renye Yan, Jikang Cheng, You Wu +9
Latent diffusion models (LDMs) enable efficient high-resolution image synthesis by denoising in a VAE-compressed latent space. However, fixed visual tokenizers can discard fine tex…
InfoDense: Density-Aware Regional Decisive Replay for Memory-Efficient Incremental Face Forgery Detection
Jikang Cheng, Hao Shen, Xueyi Zhang +4
The rapid evolution of face forgery techniques has introduced an increasing variety of manipulations. Incremental Face Forgery Detection (IFFD), which incrementally adds new forger…
Do Less, Achieve More: Do We Need Every-Step Optimization for RL Fine-tuning of Diffusion Models?
Renye Yan, Jikang Cheng, Shikun Sun +7
Despite strong image-generation performance, diffusion models' reconstruction objectives limit alignment with human preferences. RL enables such alignment through explicit rewards.…
A Sanity Check for Multi-In-Domain Face Forgery Detection in the Real World
Jikang Cheng, Renye Yan, Zhiyuan Yan +5
Existing methods for deepfake detection aim to develop generalizable detectors. Although "generalizable" is the ultimate target once and for all, with limited training forgeries an…