activity
20212026
most citedR2RNet: Low-light Image Enhancement via Real-low to Real-normal Network

411 citations · 415 across the 11 of their papers we have counts for

collaborators

11 papers

cs.RO2026

FutureRTC: Real-Time Robot Execution with Anticipatory-Conditioned Action Chunking

Hai Jiang, Yixian Zou, Binbin Liang +3

Real-time deployment of Vision-Language-Action (VLA) policies necessitates asynchronous execution, wherein subsequent action chunks are computed concurrently with the execution of…

cs.CV2026

CamFlow+: Hybrid Motion Bases for 2D Camera Motion Estimation with Stabilization Applications

Haipeng Li, Zhen Liu, Zhanglei Yang +6

Estimating 2D camera motion is fundamental to computer vision and computational photography. Existing homography-based methods work well for planar scenes or pure rotation, but str…

cs.CV2026

ZeroIDIR: Zero-Reference Illumination Degradation Image Restoration with Perturbed Consistency Diffusion Models

Hai Jiang, Zhen Liu, Yinjie Lei +3

In this paper, we propose a zero-reference diffusion-based framework, named ZeroIDIR, for illumination degradation image restoration, which decouples the restoration process into a…

cs.CV2026

RAW-Flow: Advancing RGB-to-RAW Image Reconstruction with Deterministic Latent Flow Matching

Zhen Liu, Diedong Feng, Hai Jiang +6

RGB-to-RAW reconstruction, or the reverse modeling of a camera Image Signal Processing (ISP) pipeline, aims to recover high-fidelity RAW data from RGB images. Despite notable progr…

eess.IV2025

Learning Arbitrary-Scale RAW Image Downscaling with Wavelet-based Recurrent Reconstruction

Yang Ren, Hai Jiang, Wei Li +5

Image downscaling is critical for efficient storage and transmission of high-resolution (HR) images. Existing learning-based methods focus on performing downscaling within the sRGB…

cs.CV2025

Learning to See in the Extremely Dark

Hai Jiang, Binhao Guan, Zhen Liu +5

Learning-based methods have made promising advances in low-light RAW image enhancement, while their capability to extremely dark scenes where the environmental illuminance drops as…

cs.CV2025

StableMotion: One-Step Motion Estimation with Diffusion Prior

Ziyi Wang, Haipeng Li, Lin Sui +5

We present StableMotion, a novel framework that leverages geometric and content priors from pretrained large-scale image diffusion models for motion estimation in single-image rect…

cs.CV2025

ISPDiffuser: Learning RAW-to-sRGB Mappings with Texture-Aware Diffusion Models and Histogram-Guided Color Consistency

Yang Ren, Hai Jiang, Menglong Yang +2

RAW-to-sRGB mapping, or the simulation of the traditional camera image signal processor (ISP), aims to generate DSLR-quality sRGB images from raw data captured by smartphone sensor…

cs.CV2024★ 3 cited

LightenDiffusion: Unsupervised Low-Light Image Enhancement with Latent-Retinex Diffusion Models

Hai Jiang, Ao Luo, Xiaohong Liu +2

In this paper, we propose a diffusion-based unsupervised framework that incorporates physically explainable Retinex theory with diffusion models for low-light image enhancement, na…

cs.CV2023★ 1 cited

Supervised Homography Learning with Realistic Dataset Generation

Hai Jiang, Haipeng Li, Songchen Han +3

In this paper, we propose an iterative framework, which consists of two phases: a generation phase and a training phase, to generate realistic training data and yield a supervised…

cs.CV2021★ 411 cited

R2RNet: Low-light Image Enhancement via Real-low to Real-normal Network

Jiang Hai, Zhu Xuan, Songchen Han +4

Images captured in weak illumination conditions could seriously degrade the image quality. Solving a series of degradation of low-light images can effectively improve the visual qu…