collaborators

7 papers

cs.LG2026

Plug-and-Play Guidance for Discrete Diffusion Models via Gradient-Informed Logit Correction

Hongkun Dou, Zike Chen, Fengji Li +2

Controllable generation with discrete diffusion models is often hindered by high computational overhead or the need for retraining. In this paper, we present \underline{\textbf{G}}…

cs.CV2026

Spatiotemporal Degradation-Aware 3D Gaussian Splatting for Realistic Underwater Scene Reconstruction

Shaohua Liu, Ning Gao, Zuoya Gu +3

Reconstructing realistic underwater scenes from underwater video remains a meaningful yet challenging task in the multimedia domain. The inherent spatiotemporal degradations in und…

cs.LG2026

Constrained Particle Seeking: Solving Diffusion Inverse Problems with Just Forward Passes

Hongkun Dou, Zike Chen, Zeyu Li +3

Diffusion models have gained prominence as powerful generative tools for solving inverse problems due to their ability to model complex data distributions. However, existing method…

cs.CV2025

DPoser-X: Diffusion Model as Robust 3D Whole-body Human Pose Prior

Junzhe Lu, Jing Lin, Hongkun Dou +8

We present DPoser-X, a diffusion-based prior model for 3D whole-body human poses. Building a versatile and robust full-body human pose prior remains challenging due to the inherent…

cs.CV2025

Global Modeling Matters: A Fast, Lightweight and Effective Baseline for Efficient Image Restoration

Xingyu Jiang, Ning Gao, Hongkun Dou +4

Natural image quality is often degraded by adverse weather conditions, significantly impairing the performance of downstream tasks. Image restoration has emerged as a core solution…

cs.LG2025

You Only Look One Step: Accelerating Backpropagation in Diffusion Sampling with Gradient Shortcuts

Hongkun Dou, Zeyu Li, Xingyu Jiang +4

Diffusion models (DMs) have recently demonstrated remarkable success in modeling large-scale data distributions. However, many downstream tasks require guiding the generated conten…