287 citations · 864 across the 71 of their papers we have counts for
71 papers
Multiple Latent Space Mapping for Compressed Dark Image Enhancement
Yi Zeng, Zhengning Wang, Yuxuan Liu +6
Dark image enhancement aims at converting dark images to normal-light images. Existing dark image enhancement methods take uncompressed dark images as inputs and achieve great perf…
GAFlow: Incorporating Gaussian Attention into Optical Flow
Ao Luo, Fan Yang, Xin Li +4
Optical flow, or the estimation of motion fields from image sequences, is one of the fundamental problems in computer vision. Unlike most pixel-wise tasks that aim at achieving con…
MEFLUT: Unsupervised 1D Lookup Tables for Multi-exposure Image Fusion
Ting Jiang, Chuan Wang, Xinpeng Li +3
In this paper, we introduce a new approach for high-quality multi-exposure image fusion (MEF). We show that the fusion weights of an exposure can be encoded into a 1D lookup table…
AccFlow: Backward Accumulation for Long-Range Optical Flow
Guangyang Wu, Xiaohong Liu, Kunming Luo +6
Recent deep learning-based optical flow estimators have exhibited impressive performance in generating local flows between consecutive frames. However, the estimation of long-range…
Low-Light Image Enhancement with Illumination-Aware Gamma Correction and Complete Image Modelling Network
Yinglong Wang, Zhen Liu, Jianzhuang Liu +2
This paper presents a novel network structure with illumination-aware gamma correction and complete image modelling to solve the low-light image enhancement problem. Low-light envi…
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…
Uncertainty Guided Adaptive Warping for Robust and Efficient Stereo Matching
Junpeng Jing, Jiankun Li, Pengfei Xiong +7
Correlation based stereo matching has achieved outstanding performance, which pursues cost volume between two feature maps. Unfortunately, current methods with a fixed model do not…
SAM-IQA: Can Segment Anything Boost Image Quality Assessment?
Xinpeng Li, Ting Jiang, Haoqiang Fan +1
Image Quality Assessment (IQA) is a challenging task that requires training on massive datasets to achieve accurate predictions. However, due to the lack of IQA data, deep learning…
Single-Image-Based Deep Learning for Segmentation of Early Esophageal Cancer Lesions
Haipeng Li, Dingrui Liu, Yu Zeng +5
Accurate segmentation of lesions is crucial for diagnosis and treatment of early esophageal cancer (EEC). However, neither traditional nor deep learning-based methods up to today c…
Low-Light Image Enhancement with Wavelet-based Diffusion Models
Hai Jiang, Ao Luo, Songchen Han +2
Diffusion models have achieved promising results in image restoration tasks, yet suffer from time-consuming, excessive computational resource consumption, and unstable restoration.…
Realistic Noise Synthesis with Diffusion Models
Qi Wu, Mingyan Han, Ting Jiang +5
Deep denoising models require extensive real-world training data, which is challenging to acquire. Current noise synthesis techniques struggle to accurately model complex noise dis…
DIPNet: Efficiency Distillation and Iterative Pruning for Image Super-Resolution
Lei Yu, Xinpeng Li, Youwei Li +4
Efficient deep learning-based approaches have achieved remarkable performance in single image super-resolution. However, recent studies on efficient super-resolution have mainly fo…
Exposure Fusion for Hand-held Camera Inputs with Optical Flow and PatchMatch
Ru Li, Guanghui Liu, Bing Zeng +1
This paper proposes a hybrid synthesis method for multi-exposure image fusion taken by hand-held cameras. Motions either due to the shaky camera or caused by dynamic scenes should…
Learning Optical Flow from Event Camera with Rendered Dataset
Xinglong Luo, Kunming Luo, Ao Luo +3
We study the problem of estimating optical flow from event cameras. One important issue is how to build a high-quality event-flow dataset with accurate event values and flow labels…
Parallax-Tolerant Unsupervised Deep Image Stitching
Lang Nie, Chunyu Lin, Kang Liao +2
Traditional image stitching approaches tend to leverage increasingly complex geometric features (point, line, edge, etc.) for better performance. However, these hand-crafted featur…
GyroFlow+: Gyroscope-Guided Unsupervised Deep Homography and Optical Flow Learning
Haipeng Li, Kunming Luo, Bing Zeng +1
Existing homography and optical flow methods are erroneous in challenging scenes, such as fog, rain, night, and snow because the basic assumptions such as brightness and gradient c…
DAS: Neural Architecture Search via Distinguishing Activation Score
Yuqiao Liu, Haipeng Li, Yanan Sun +1
Neural Architecture Search (NAS) is an automatic technique that can search for well-performed architectures for a specific task. Although NAS surpasses human-designed architecture…
RAGO: Recurrent Graph Optimizer For Multiple Rotation Averaging
Heng Li, Zhaopeng Cui, Shuaicheng Liu +1
This paper proposes a deep recurrent Rotation Averaging Graph Optimizer (RAGO) for Multiple Rotation Averaging (MRA). Conventional optimization-based methods usually fail to produc…
Semi-supervised Deep Large-baseline Homography Estimation with Progressive Equivalence Constraint
Hai Jiang, Haipeng Li, Yuhang Lu +2
Homography estimation is erroneous in the case of large-baseline due to the low image overlay and limited receptive field. To address it, we propose a progressive estimation strate…
Minimum Latency Deep Online Video Stabilization
Zhuofan Zhang, Zhen Liu, Ping Tan +2
We present a novel camera path optimization framework for the task of online video stabilization. Typically, a stabilization pipeline consists of three steps: motion estimating, pa…
Efficient and Accurate Quantized Image Super-Resolution on Mobile NPUs, Mobile AI & AIM 2022 challenge: Report
Andrey Ignatov, Radu Timofte, Maurizio Denna +93
Image super-resolution is a common task on mobile and IoT devices, where one often needs to upscale and enhance low-resolution images and video frames. While numerous solutions hav…
Fast Nearest Convolution for Real-Time Efficient Image Super-Resolution
Ziwei Luo, Youwei Li, Lei Yu +4
Deep learning-based single image super-resolution (SISR) approaches have drawn much attention and achieved remarkable success on modern advanced GPUs. However, most state-of-the-ar…
Ghost-free High Dynamic Range Imaging with Context-aware Transformer
Zhen Liu, Yinglong Wang, Bing Zeng +1
High dynamic range (HDR) deghosting algorithms aim to generate ghost-free HDR images with realistic details. Restricted by the locality of the receptive field, existing CNN-based m…
RealFlow: EM-based Realistic Optical Flow Dataset Generation from Videos
Yunhui Han, Kunming Luo, Ao Luo +4
Obtaining the ground truth labels from a video is challenging since the manual annotation of pixel-wise flow labels is prohibitively expensive and laborious. Besides, existing appr…