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most citedBrightness Perceiving for Recursive Low-Light Image Enhancement

23 citations · 28 across the 20 of their papers we have counts for

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6 papers · 1 filter

cs.CV2025

VividFace: High-Quality and Efficient One-Step Diffusion For Video Face Enhancement

Shulian Zhang, Yong Guo, Long Peng +6

Video Face Enhancement (VFE) aims to restore high-quality facial regions from degraded video sequences, enabling a wide range of practical applications. Despite substantial progres…

cs.CV2025

RobustGS: Unified Boosting of Feedforward 3D Gaussian Splatting under Low-Quality Conditions

Anran Wu, Long Peng, Xin Di +6

Feedforward 3D Gaussian Splatting (3DGS) overcomes the limitations of optimization-based 3DGS by enabling fast and high-quality reconstruction without the need for per-scene optimi…

cs.CV2025

PMQ-VE: Progressive Multi-Frame Quantization for Video Enhancement

ZhanFeng Feng, Long Peng, Xin Di +7

Multi-frame video enhancement tasks aim to improve the spatial and temporal resolution and quality of video sequences by leveraging temporal information from multiple frames, which…

cs.CV2025★ 23 cited

Brightness Perceiving for Recursive Low-Light Image Enhancement

Haodian Wang, Long Peng, Yuejin Sun +3

Due to the wide dynamic range in real low-light scenes, there will be large differences in the degree of contrast degradation and detail blurring of captured images, making it diff…

cs.CV2025

Pixel to Gaussian: Ultra-Fast Continuous Super-Resolution with 2D Gaussian Modeling

Long Peng, Anran Wu, Wenbo Li +9

Arbitrary-scale super-resolution (ASSR) aims to reconstruct high-resolution (HR) images from low-resolution (LR) inputs with arbitrary upsampling factors using a single model, addr…

cs.CV2025

Directing Mamba to Complex Textures: An Efficient Texture-Aware State Space Model for Image Restoration

Long Peng, Xin Di, Zhanfeng Feng +6

Image restoration aims to recover details and enhance contrast in degraded images. With the growing demand for high-quality imaging (\textit{e.g.}, 4K and 8K), achieving a balance…