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20212026
most citedYou Only Need 90K Parameters to Adapt Light: A Light Weight Transformer for Image Enhancement and Exposure Correction

80 citations · 137 across the 33 of their papers we have counts for

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13 papers · 1 filter

cs.RO2026

RawVLA: Embodied Neural Image Signal Processor For Robotic Manipulation

Shuhong Liu, Heng Zhou, Lingfeng Qian +7

Vision-language-action (VLA) models typically operate on RGB images produced by a fixed camera image signal processor (ISP), leaving the imaging pipeline outside the learning and e…

cs.CV2026

ASTRA-SR: Atmospheric Seeing and Turbulence Restoration for Astronomical Image Super-Resolution

Xining Ge, Ziteng Cui, Shuhong Liu

Ground-based planetary imaging suffers from atmospheric turbulence, sensor noise, and limited sampling, making restoration a joint denoising, deblurring, and super-resolution probl…

cs.CV2026

FujinSplat: Seeing Through Smoke with RAW-Domain Gaussian Splatting

Gengjia Chang, Ziteng Cui, Shuhong Liu

The appearance of a smoky scene is shaped by two processes that a camera records together: the participating medium alters scene radiance in a view-dependent way, and the image sig…

cs.CV2026

CapTalk: Text-Guided Stylization and Speech-Driven 3D Head Animation

Xuangeng Chu, Yuan Gan, Ziteng Cui +4

Audio-driven 3D facial animation aims to generate synchronized lip movements and vivid facial expressions from arbitrary audio clips. While existing methods can produce synchronize…

cs.CV2026

RAWild: Sensor-Agnostic RAW Object Detection via Physics-Guided Curve and Grid Modeling

Shuhong Liu, Gengjia Chang, Jun Liu +4

Camera sensor RAW data offers intrinsic advantages for object detection, including deeper bit depth, preserved physical information, and freedom from image signal processor (ISP) d…

cs.CV2026

FluxFlow: Conservative Flow-Matching for Astronomical Image Super-Resolution

Shuhong Liu, Xining Ge, Ziteng Cui +8

Ground-to-space astronomical super-resolution requires recovering space-quality images from ground-based observations that are simultaneously limited by pixel sampling resolution a…

cs.CV2026

NTIRE 2026 3D Restoration and Reconstruction in Real-world Adverse Conditions: RealX3D Challenge Results

Shuhong Liu, Chenyu Bao, Ziteng Cui +103

This paper presents a comprehensive review of the NTIRE 2026 3D Restoration and Reconstruction (3DRR) Challenge, detailing the proposed methods and results. The challenge seeks to…

cs.CV2026

The Eleventh NTIRE 2026 Efficient Super-Resolution Challenge Report

Bin Ren, Hang Guo, Yan Shu +60

This paper reviews the NTIRE 2026 challenge on efficient single-image super-resolution with a focus on the proposed solutions and results. The aim of this challenge is to devise a…

cs.CV2026

MERIT: Multi-domain Efficient RAW Image Translation

Wenjun Huang, Shenghao Fu, Yian Jin +10

RAW images captured by different camera sensors exhibit substantial domain shifts due to varying spectral responses, noise characteristics, and tone behaviors, complicating their d…

cs.CV2026

Unifying Color and Lightness Correction with View-Adaptive Curve Adjustment for Robust 3D Novel View Synthesis

Ziteng Cui, Shuhong Liu, Xiaoyu Dong +4

High-quality image acquisition in real-world environments remains challenging due to complex illumination variations and inherent limitations of camera imaging pipelines. These iss…

cs.CV2026

Robust Self-Supervised Cross-Modal Super-Resolution against Real-World Misaligned Observations

Xiaoyu Dong, Jiahuan Li, Ziteng Cui +1

Cross-modal super-resolution (SR) on real-world misaligned data is challenging, as only unlabeled low-resolution (LR) source and high-resolution (HR) guide images with complex spat…

cs.CV2026

RealX3D: A Physically-Degraded 3D Benchmark for Multi-view Visual Restoration and Reconstruction

Shuhong Liu, Chenyu Bao, Ziteng Cui +11

We introduce RealX3D, a real-capture benchmark for multi-view visual restoration and 3D reconstruction under diverse physical degradations. RealX3D groups corruptions into four fam…

astro-ph.IM2026

Denoising the Deep Sky: Physics-Based CCD Noise Formation for Astronomical Imaging

Shuhong Liu, Xining Ge, Ziying Gu +7

Astronomical imaging remains noise-limited under practical observing conditions. Standard calibration pipelines remove structured artifacts but largely leave stochastic noise unres…