94 citations · 100 across the 26 of their papers we have counts for
19 papers · 1 filter
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…
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…
X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras
Heng Zhou, Shuhong Liu, Yonghao He +6
We present X-lens, a compact feed-forward model for metric depth estimation from a variable number of calibrated fisheye and pinhole views. To support real-time downstream percepti…
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…
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…
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…
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…
Training-Free Model Ensemble for Single-Image Super-Resolution via Strong-Branch Compensation
Gengjia Chang, Xining Ge, Weijun Yuan +4
Single-image super-resolution has progressed from deep convolutional baselines to stronger Transformer and state-space architectures, yet the corresponding performance gains typica…
Beyond Model Design: Data-Centric Training and Self-Ensemble for Gaussian Color Image Denoising
Gengjia Chang, Xining Ge, Weijun Yuan +4
This paper presents our solution to the NTIRE 2026 Image Denoising Challenge (Gaussian color image denoising at fixed noise level ). Rather than proposing a new restoration…
Dual-Branch Remote Sensing Infrared Image Super-Resolution
Xining Ge, Gengjia Chang, Weijun Yuan +6
Remote sensing infrared image super-resolution aims to recover sharper thermal observations from low-resolution inputs while preserving target contours, scene layout, and radiometr…
CLIP-Guided Data Augmentation for Night-Time Image Dehazing
Xining Ge, Weijun Yuan, Gengjia Chang +2
Nighttime image dehazing faces a more complex degradation pattern than its daytime counterpart, as haze scattering couples with low illumination, non-uniform lighting, and strong l…
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…
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…
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…
I2-NeRF: Learning Neural Radiance Fields Under Physically-Grounded Media Interactions
Shuhong Liu, Lin Gu, Ziteng Cui +2
Participating in efforts to endow generative AI with the 3D physical world perception, we propose I2-NeRF, a novel neural radiance field framework that enhances isometric and isotr…
DeRainGS: Gaussian Splatting for Enhanced Scene Reconstruction in Rainy Environments
Shuhong Liu, Xiang Chen, Hongming Chen +2
Reconstruction under adverse rainy conditions poses significant challenges due to reduced visibility and the distortion of visual perception. These conditions can severely impair t…
MoD-SLAM: Monocular Dense Mapping for Unbounded 3D Scene Reconstruction
Heng Zhou, Zhetao Guo, Shuhong Liu +4
Monocular SLAM has received a lot of attention due to its simple RGB inputs and the lifting of complex sensor constraints. However, existing monocular SLAM systems are designed for…
SGS-SLAM: Semantic Gaussian Splatting For Neural Dense SLAM
Mingrui Li, Shuhong Liu, Heng Zhou +4
We present SGS-SLAM, the first semantic visual SLAM system based on Gaussian Splatting. It incorporates appearance, geometry, and semantic features through multi-channel optimizati…
CEIR: Concept-based Explainable Image Representation Learning
Yan Cui, Shuhong Liu, Liuzhuozheng Li +1
In modern machine learning, the trend of harnessing self-supervised learning to derive high-quality representations without label dependency has garnered significant attention. How…