activity
20242026
collaborators

24 papers

cs.CV2026

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.…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

COLLAR: Cascaded Object-Level Latent Refinement for High-Fidelity Conditional Generation

Xinlong Zhang, Jia Wei, Xiaoyu Zhang +3

Achieving high-fidelity object-level control in Diffusion Transformers remains a significant challenge despite the introduction of structural priors like depth and Canny maps. Curr…

cs.CV2026

GeoRect4D: Geometry-Compatible Generative Rectification for Dynamic Sparse-View 3D Reconstruction

Zhenlong Wu, Zihan Zheng, Xuanxuan Wang +7

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…