6 papers
An Iteration-Free Fixed-Point Estimator for Diffusion Inversion
Yifei Chen, Kaiyu Song, Yan Pan +3
Diffusion inversion aims to recover the initial noise corresponding to a given image such that this noise can reconstruct the original image through the denoising diffusion process…
Topology Sculptor, Shape Refiner: Discrete Diffusion Model for High-Fidelity 3D Meshes Generation
Kaiyu Song, Hanjiang Lai, Yaqing Zhang +3
In this paper, we introduce Topology Sculptor, Shape Refiner (TSSR), a novel method for generating high-quality, artist-style 3D meshes based on Discrete Diffusion Models (DDMs). O…
Flow Matching Posterior Sampling: A Training-free Conditional Generation for Flow Matching
Kaiyu Song, Hanjiang Lai, Yan Pan +2
Training-free conditional generation based on flow matching aims to leverage pre-trained unconditional flow matching models to perform conditional generation without retraining. Re…
Rethinking Oversaturation in Classifier-Free Guidance via Low Frequency
Kaiyu Song, Hanjiang Lai
Classifier-free guidance (CFG) succeeds in condition diffusion models that use a guidance scale to balance the influence of conditional and unconditional terms. A high guidance sca…
Two Simple Principles for Diffusion-Based Test-Time Adaptation
Kaiyu Song, Hanjiang Lai, Yan Pan +2
Recently, diffusion-based test-time adaptations (TTA) have shown great advances, which leverage a diffusion model to map the images in the unknown test domain to the training domai…
Leveraging Previous Steps: A Training-free Fast Solver for Flow Diffusion
Kaiyu Song, Hanjiang Lai
Flow diffusion models (FDMs) have recently shown potential in generation tasks due to the high generation quality. However, the current ordinary differential equation (ODE) solver…