270 citations · 436 across the 18 of their papers we have counts for
19 papers
FlowPainter: Inpainting Optical Flow via Confidence-Guided Completion
Yuang Meng, Chenyang Wu, Xianshun Liu +7
Existing optical flow methods broadly follow two paradigms: iterative optimization and diffusion-based estimation. Iterative methods, exemplified by RAFT, achieve high accuracy thr…
Perceiving Better Moments: Cover Frame Reselection and Enhancement for Live Photos with the Live2K Dataset
Junyu Lou, Kai Chen, Weiyi You +3
Modern smartphones capture Live Photos, short video bursts surrounding a still image, offering a dynamic and engaging photographic experience. However, the cover photo and video co…
ExpoMotion: A Large-Scale Benchmark and A Householder Projection Network for Multi-Exposure Fusion
Yao Liu, Lishen Qu, Shihao Zhou +6
Multi-Exposure Fusion (MEF) effectively extends dynamic range, but practical deployment is hindered by motion-induced ghosting and the scarcity of high-quality dynamic benchmarks.…
It Takes Two: A Duet of Periodicity and Directionality for Burst Flicker Removal
Lishen Qu, Shihao Zhou, Jie Liang +3
Flicker artifacts, arising from unstable illumination and row-wise exposure inconsistencies, pose a significant challenge in short-exposure photography, severely degrading image qu…
Reverse Convolution and Its Applications to Image Restoration
Xuhong Huang, Shiqi Liu, Kai Zhang +4
Convolution and transposed convolution are fundamental operators widely used in neural networks. However, transposed convolution (a.k.a. deconvolution) does not serve as a true inv…
MaSS13K: A Matting-level Semantic Segmentation Benchmark
Chenxi Xie, Minghan Li, Hui Zeng +2
High-resolution semantic segmentation is essential for applications such as image editing, bokeh imaging, AR/VR, etc. Unfortunately, existing datasets often have limited resolution…
NTIRE 2024 Restore Any Image Model (RAIM) in the Wild Challenge
Jie Liang, Radu Timofte, Qiaosi Yi +6
In this paper, we review the NTIRE 2024 challenge on Restore Any Image Model (RAIM) in the Wild. The RAIM challenge constructed a benchmark for image restoration in the wild, inclu…
Guided Image Restoration via Simultaneous Feature and Image Guided Fusion
Xinyi Liu, Qian Zhao, Jie Liang +3
Guided image restoration (GIR), such as guided depth map super-resolution and pan-sharpening, aims to enhance a target image using guidance information from another image of the sa…
Human Guided Ground-truth Generation for Realistic Image Super-resolution
Du Chen, Jie Liang, Xindong Zhang +3
How to generate the ground-truth (GT) image is a critical issue for training realistic image super-resolution (Real-ISR) models. Existing methods mostly take a set of high-resoluti…
Efficient and Degradation-Adaptive Network for Real-World Image Super-Resolution
Jie Liang, Hui Zeng, Lei Zhang
Efficient and effective real-world image super-resolution (Real-ISR) is a challenging task due to the unknown complex degradation of real-world images and the limited computation r…
Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-Resolution
Jie Liang, Hui Zeng, Lei Zhang
Single image super-resolution (SISR) with generative adversarial networks (GAN) has recently attracted increasing attention due to its potentials to generate rich details. However,…
Efficient Long-Range Attention Network for Image Super-resolution
Xindong Zhang, Hui Zeng, Shi Guo +1
Recently, transformer-based methods have demonstrated impressive results in various vision tasks, including image super-resolution (SR), by exploiting the self-attention (SA) for f…
High-Resolution Photorealistic Image Translation in Real-Time: A Laplacian Pyramid Translation Network
Jie Liang, Hui Zeng, Lei Zhang
Existing image-to-image translation (I2IT) methods are either constrained to low-resolution images or long inference time due to their heavy computational burden on the convolution…
PPR10K: A Large-Scale Portrait Photo Retouching Dataset with Human-Region Mask and Group-Level Consistency
Jie Liang, Hui Zeng, Miaomiao Cui +2
Different from general photo retouching tasks, portrait photo retouching (PPR), which aims to enhance the visual quality of a collection of flat-looking portrait photos, has its sp…
Learning Image-adaptive 3D Lookup Tables for High Performance Photo Enhancement in Real-time
Hui Zeng, Jianrui Cai, Lida Li +2
Recent years have witnessed the increasing popularity of learning based methods to enhance the color and tone of photos. However, many existing photo enhancement methods either del…
Grid Anchor based Image Cropping: A New Benchmark and An Efficient Model
Hui Zeng, Lida Li, Zisheng Cao +1
Image cropping aims to improve the composition as well as aesthetic quality of an image by removing extraneous content from it. Most of the existing image cropping databases provid…
Reliable and Efficient Image Cropping: A Grid Anchor based Approach
Hui Zeng, Lida Li, Zisheng Cao +1
Image cropping aims to improve the composition as well as aesthetic quality of an image by removing extraneous content from it. Existing image cropping databases provide only one o…
Toward Real-World Single Image Super-Resolution: A New Benchmark and A New Model
Jianrui Cai, Hui Zeng, Hongwei Yong +2
Most of the existing learning-based single image superresolution (SISR) methods are trained and evaluated on simulated datasets, where the low-resolution (LR) images are generated…
A Probabilistic Quality Representation Approach to Deep Blind Image Quality Prediction
Hui Zeng, Lei Zhang, Alan C. Bovik
Blind image quality assessment (BIQA) remains a very challenging problem due to the unavailability of a reference image. Deep learning based BIQA methods have been attracting incre…