activity
20242026
collaborators

6 papers

cs.CV2026

Prompt-SID: Learning Structural Representation Prompt via Latent Diffusion for Single-Image Denoising

Huaqiu Li, Wang Zhang, Xiaowan Hu +3

Many studies have concentrated on constructing supervised models utilizing paired datasets for image denoising, which proves to be expensive and time-consuming. Current self-superv…

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

Interpretable Unsupervised Joint Denoising and Enhancement for Real-World low-light Scenarios

Huaqiu Li, Xiaowan Hu, Haoqian Wang

Real-world low-light images often suffer from complex degradations such as local overexposure, low brightness, noise, and uneven illumination. Supervised methods tend to overfit to…

cs.CV2025

HumanMM: Global Human Motion Recovery from Multi-shot Videos

Yuhong Zhang, Guanlin Wu, Ling-Hao Chen +8

In this paper, we present a novel framework designed to reconstruct long-sequence 3D human motion in the world coordinates from in-the-wild videos with multiple shot transitions. S…

cs.CV2025

Motion-X++: A Large-Scale Multimodal 3D Whole-body Human Motion Dataset

Yuhong Zhang, Jing Lin, Ailing Zeng +7

In this paper, we introduce Motion-X++, a large-scale multimodal 3D expressive whole-body human motion dataset. Existing motion datasets predominantly capture body-only poses, lack…

cs.CV2024

Spatiotemporal Blind-Spot Network with Calibrated Flow Alignment for Self-Supervised Video Denoising

Zikang Chen, Tao Jiang, Xiaowan Hu +3

Self-supervised video denoising aims to remove noise from videos without relying on ground truth data, leveraging the video itself to recover clean frames. Existing methods often r…