activity
20202026
most citedMDCN: Multi-scale Dense Cross Network for Image Super-Resolution

7 citations · 24 across the 11 of their papers we have counts for

collaborators

12 papers

cs.CV2026

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…

cs.CV20253 cited

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…

cs.CV2024

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…

cs.CV2023

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…

eess.IV2023

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…

cs.CV20234 cited

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…