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…
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…
Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization
Baoshun Tong, Kaiyu Song, Hanjiang Lai
Few-shot out-of-distribution (OOD) detection aims to detect OOD images from unseen classes with only a few labeled in-distribution (ID) images. To detect OOD images and classify ID…
Test-time Alignment-Enhanced Adapter for Vision-Language Models
Baoshun Tong, Kaiyu Song, Hanjiang Lai
Test-time adaptation with pre-trained vision-language models (VLMs) has attracted increasing attention for tackling the issue of distribution shift during the test phase. While pri…
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…