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20232026
most citedReconstruct-and-Generate Diffusion Model for Detail-Preserving Image Denoising

2 citations · 2 across the 5 of their papers we have counts for

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cs.CV2026

CubeComposer: Spatio-Temporal Autoregressive 4K 360° Video Generation from Perspective Video

Lingen Li, Guangzhi Wang, Xiaoyu Li +5

Generating high-quality 360° panoramic videos from perspective input is one of the crucial applications for virtual reality (VR), whereby high-resolution videos are especially impo…

cs.CV2025

PolarFree: Polarization-based Reflection-free Imaging

Mingde Yao, Menglu Wang, King-Man Tam +3

Reflection removal is challenging due to complex light interactions, where reflections obscure important details and hinder scene understanding. Polarization naturally provides a p…

cs.CV2024

NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images

Lingen Li, Zhaoyang Zhang, Yaowei Li +7

Recent advancements in generative models have significantly improved novel view synthesis (NVS) from multi-view data. However, existing methods depend on external multi-view alignm…

cs.CV2024

Uni-ISP: Toward Unifying the Learning of ISPs from Multiple Mobile Cameras

Lingen Li, Mingde Yao, Xingyu Meng +3

Modern end-to-end image signal processors (ISPs) can learn complex mappings from RAW/XYZ data to sRGB (and vice versa), opening new possibilities in image processing. However, the…

cs.CV20232 cited

Reconstruct-and-Generate Diffusion Model for Detail-Preserving Image Denoising

Yujin Wang, Lingen Li, Tianfan Xue +1

Image denoising is a fundamental and challenging task in the field of computer vision. Most supervised denoising methods learn to reconstruct clean images from noisy inputs, which…