7 citations · 29 across the 12 of their papers we have counts for
13 papers
QMoP: Query Guided Mixture-of-Projector for Efficient Visual Token Compression
Zhongyang Li, Yaqian Li, Faming Fang +6
Multimodal large language models suffer from severe computational and memory bottlenecks, as the number of visual tokens far exceeds that of textual tokens. While recent methods em…
First-order State Space Model for Lightweight Image Super-resolution
Yujie Zhu, Xinyi Zhang, Yekai Lu +3
State space models (SSMs), particularly Mamba, have shown promise in NLP tasks and are increasingly applied to vision tasks. However, most Mamba-based vision models focus on networ…
Harmonizing knowledge Transfer in Neural Network with Unified Distillation
Yaomin Huang, Zaomin Yan, Chaomin Shen +2
Knowledge distillation (KD), known for its ability to transfer knowledge from a cumbersome network (teacher) to a lightweight one (student) without altering the architecture, has b…
Three-Stage Cascade Framework for Blurry Video Frame Interpolation
Pengcheng Lei, Zaoming Yan, Tingting Wang +2
Blurry video frame interpolation (BVFI) aims to generate high-frame-rate clear videos from low-frame-rate blurry videos, is a challenging but important topic in the computer vision…
Deep Unfolding Convolutional Dictionary Model for Multi-Contrast MRI Super-resolution and Reconstruction
Pengcheng Lei, Faming Fang, Guixu Zhang +1
Magnetic resonance imaging (MRI) tasks often involve multiple contrasts. Recently, numerous deep learning-based multi-contrast MRI super-resolution (SR) and reconstruction methods…
Deep Richardson-Lucy Deconvolution for Low-Light Image Deblurring
Liang Chen, Jiawei Zhang, Zhenhua Li +4
Images taken under the low-light condition often contain blur and saturated pixels at the same time. Deblurring images with saturated pixels is quite challenging. Because of the li…
Flow Guidance Deformable Compensation Network for Video Frame Interpolation
Pengcheng Lei, Faming Fang, Guixu Zhang
Motion-based video frame interpolation (VFI) methods have made remarkable progress with the development of deep convolutional networks over the past years. While their performance…
Multiple Degradation and Reconstruction Network for Single Image Denoising via Knowledge Distillation
Juncheng Li, Hanhui Yang, Qiaosi Yi +4
Single image denoising (SID) has achieved significant breakthroughs with the development of deep learning. However, the proposed methods are often accompanied by plenty of paramete…
Contrastive Learning for Local and Global Learning MRI Reconstruction
Qiaosi Yi, Jinhao Liu, Le Hu +2
Magnetic Resonance Imaging (MRI) is an important medical imaging modality, while it requires a long acquisition time. To reduce the acquisition time, various methods have been prop…
Structure-Preserving Deraining with Residue Channel Prior Guidance
Qiaosi Yi, Juncheng Li, Qinyan Dai +3
Single image deraining is important for many high-level computer vision tasks since the rain streaks can severely degrade the visibility of images, thereby affecting the recognitio…
Feedback Network for Mutually Boosted Stereo Image Super-Resolution and Disparity Estimation
Qinyan Dai, Juncheng Li, Qiaosi Yi +2
Under stereo settings, the problem of image super-resolution (SR) and disparity estimation are interrelated that the result of each problem could help to solve the other. The effec…
Efficient and Accurate Multi-scale Topological Network for Single Image Dehazing
Qiaosi Yi, Juncheng Li, Faming Fang +2
Single image dehazing is a challenging ill-posed problem that has drawn significant attention in the last few years. Recently, convolutional neural networks have achieved great suc…
MDCN: Multi-scale Dense Cross Network for Image Super-Resolution
Juncheng Li, Faming Fang, Jiaqian Li +2
Convolutional neural networks have been proven to be of great benefit for single-image super-resolution (SISR). However, previous works do not make full use of multi-scale features…