13 citations · 31 across the 21 of their papers we have counts for
23 papers
DuSRFlow: Dual-Lens Super-Resolution via Parallax-Aware Flow Estimation and Complementary Reference Warping
Fangpu Zhang, Huanjing Yue, Zifan Cui +3
Dual-lens super-resolution (DuSR) aims to enhance a wide-angle low-resolution (LR) image by exploiting a telephoto reference (Ref) image. A central challenge in DuSR is reliable re…
DSDNet: Raw Domain Demoiréing via Dual Color-Space Synergy
Qirui Yang, Fangpu Zhang, Yeying Jin +4
With the rapid advancement of mobile imaging, capturing screens using smartphones has become a prevalent practice in distance learning and conference recording. However, moiré arti…
Learning Adaptive Lighting via Channel-Aware Guidance
Qirui Yang, Peng-Tao Jiang, Hao Zhang +4
Learning lighting adaptation is a crucial step in achieving good visual perception and supporting downstream vision tasks. Current research often addresses individual light-related…
Learning Differential Pyramid Representation for Tone Mapping
Qirui Yang, Yinbo Li, Yihao Liu +5
Existing tone mapping methods operate on downsampled inputs and rely on handcrafted pyramids to recover high-frequency details. These designs typically fail to preserve fine textur…
Zero-Shot Video Restoration and Enhancement Using Pre-Trained Image Diffusion Model
Cong Cao, Huanjing Yue, Xin Liu +1
Diffusion-based zero-shot image restoration and enhancement models have achieved great success in various tasks of image restoration and enhancement. However, directly applying the…
DeeDSR: Towards Real-World Image Super-Resolution via Degradation-Aware Stable Diffusion
Chunyang Bi, Xin Luo, Sheng Shen +3
Diffusion models, known for their powerful generative capabilities, play a crucial role in addressing real-world super-resolution challenges. However, these models often focus on i…
AUFormer: Vision Transformers are Parameter-Efficient Facial Action Unit Detectors
Kaishen Yuan, Zitong Yu, Xin Liu +3
Facial Action Units (AU) is a vital concept in the realm of affective computing, and AU detection has always been a hot research topic. Existing methods suffer from overfitting iss…
A Simple yet Effective Network based on Vision Transformer for Camouflaged Object and Salient Object Detection
Chao Hao, Zitong Yu, Xin Liu +3
Camouflaged object detection (COD) and salient object detection (SOD) are two distinct yet closely-related computer vision tasks widely studied during the past decades. Though shar…
KeDuSR: Real-World Dual-Lens Super-Resolution via Kernel-Free Matching
Huanjing Yue, Zifan Cui, Kun Li +1
Dual-lens super-resolution (SR) is a practical scenario for reference (Ref) based SR by utilizing the telephoto image (Ref) to assist the super-resolution of the low-resolution wid…
Learning to See Low-Light Images via Feature Domain Adaptation
Qirui Yang, Qihua Cheng, Huanjing Yue +3
Raw low light image enhancement (LLIE) has achieved much better performance than the sRGB domain enhancement methods due to the merits of raw data. However, the ambiguity between n…
RISAM: Referring Image Segmentation via Mutual-Aware Attention Features
Mengxi Zhang, Yiming Liu, Xiangjun Yin +2
Referring image segmentation (RIS) aims to segment a particular region based on a language expression prompt. Existing methods incorporate linguistic features into visual features…
Recaptured Raw Screen Image and Video Demoiréing via Channel and Spatial Modulations
Huanjing Yue, Yijia Cheng, Xin Liu +1
Capturing screen contents by smartphone cameras has become a common way for information sharing. However, these images and videos are often degraded by moiré patterns, which are ca…
Multi-scale Promoted Self-adjusting Correlation Learning for Facial Action Unit Detection
Xin Liu, Kaishen Yuan, Xuesong Niu +4
Facial Action Unit (AU) detection is a crucial task in affective computing and social robotics as it helps to identify emotions expressed through facial expressions. Anatomically,…
rPPG-MAE: Self-supervised Pre-training with Masked Autoencoders for Remote Physiological Measurement
Xin Liu, Yuting Zhang, Zitong Yu +3
Remote photoplethysmography (rPPG) is an important technique for perceiving human vital signs, which has received extensive attention. For a long time, researchers have focused on…
Physics-Informed Ensemble Representation for Light-Field Image Super-Resolution
Manchang Jin, Gaosheng Liu, Kunshu Hu +3
Recent learning-based approaches have achieved significant progress in light field (LF) image super-resolution (SR) by exploring convolution-based or transformer-based network stru…
RViDeformer: Efficient Raw Video Denoising Transformer with a Larger Benchmark Dataset
Huanjing Yue, Cong Cao, Lei Liao +1
In recent years, raw video denoising has garnered increased attention due to the consistency with the imaging process and well-studied noise modeling in the raw domain. However, tw…
HDR Video Reconstruction with a Large Dynamic Dataset in Raw and sRGB Domains
Huanjing Yue, Yubo Peng, Biting Yu +3
High dynamic range (HDR) video reconstruction is attracting more and more attention due to the superior visual quality compared with those of low dynamic range (LDR) videos. The av…
Unsupervised HDR Image and Video Tone Mapping via Contrastive Learning
Cong Cao, Huanjing Yue, Xin Liu +1
Capturing high dynamic range (HDR) images (videos) is attractive because it can reveal the details in both dark and bright regions. Since the mainstream screens only support low dy…
ITSRN++: Stronger and Better Implicit Transformer Network for Continuous Screen Content Image Super-Resolution
Sheng Shen, Huanjing Yue, Jingyu Yang +1
Nowadays, online screen sharing and remote cooperation are becoming ubiquitous. However, the screen content may be downsampled and compressed during transmission, while it may be d…
Real-RawVSR: Real-World Raw Video Super-Resolution with a Benchmark Dataset
Huanjing Yue, Zhiming Zhang, Jingyu Yang
In recent years, real image super-resolution (SR) has achieved promising results due to the development of SR datasets and corresponding real SR methods. In contrast, the field of…
FOF: Learning Fourier Occupancy Field for Monocular Real-time Human Reconstruction
Qiao Feng, Yebin Liu, Yu-Kun Lai +2
The advent of deep learning has led to significant progress in monocular human reconstruction. However, existing representations, such as parametric models, voxel grids, meshes and…
Adversarial Dual-Student with Differentiable Spatial Warping for Semi-Supervised Semantic Segmentation
Cong Cao, Tianwei Lin, Dongliang He +4
A common challenge posed to robust semantic segmentation is the expensive data annotation cost. Existing semi-supervised solutions show great potential for solving this problem. Th…
FPCR-Net: Feature Pyramidal Correlation and Residual Reconstruction for Optical Flow Estimation
Xiaolin Song, Yuyang Zhao, Jingyu Yang +2
Optical flow estimation is an important yet challenging problem in the field of video analytics. The features of different semantics levels/layers of a convolutional neural network…