6 citations · 8 across the 20 of their papers we have counts for
23 papers
GenSplatCodec: Feed-Forward Gaussian Splatting Compression via One-Step Diffusion
Qiang Hu, Zhenlong Wu, Lei Huang +3
Feed-forward 3D Gaussian Splatting (3DGS) enables scalable scene reconstruction without per-scene optimization, yet produces dense Gaussians that are costly to store and transmit.…
DTI: Dynamic Trajectory Initialization for Generative Face Video Super-Resolution
Yingwei Tang, Chen Yan, Wendi Liu +2
As the most perceptually powerful Face Video Super-Resolution (FVSR) method, existing works in Generative FVSR (GFVSR) mainly exploit the generative prior of pretrained diffusion m…
TEASR: Training-Efficient Any-Step Diffusion Transformer for Real-World Image Super-Resolution
Xiang Gao, Chenxin Zhu, Yushun Fang +2
Diffusion models excel in Real-World Image Super-Resolution (Real-ISR) due to their powerful generative priors but suffer from slow iterative sampling. Although existing one-step d…
LL-Bench: Rethinking Low-Level Vision Evaluation in the Era of Large-Scale Generative Models
Lu Liu, Huiyu Duan, Chenxin Zhu +6
Large-scale generative models have demonstrated remarkable capabilities across image generation and editing tasks. However, their performance in low-level vision tasks, which requi…
GeoRect4D: Geometry-Compatible Generative Rectification for Dynamic Sparse-View 3D Reconstruction
Zhenlong Wu, Zihan Zheng, Xuanxuan Wang +5
Reconstructing dynamic 3D scenes from sparse multi-view videos is highly ill-posed, often leading to geometric collapse, trajectory drift, and floating artifacts. Recent attempts i…
A2BFR: Attribute-Aware Blind Face Restoration
Chenxin Zhu, Yushun Fang, Lu Liu +5
Blind face restoration (BFR) aims to recover high-quality facial images from degraded inputs, yet its inherently ill-posed nature leads to ambiguous and uncontrollable solutions. R…