activity
20172022
most citedTEINet: Towards an Efficient Architecture for Video Recognition

28 citations · 81 across the 9 of their papers we have counts for

collaborators

10 papers

cs.CV20226 cited

IFRNet: Intermediate Feature Refine Network for Efficient Frame Interpolation

Lingtong Kong, Boyuan Jiang, Donghao Luo +5

Prevailing video frame interpolation algorithms, that generate the intermediate frames from consecutive inputs, typically rely on complex model architectures with heavy parameters…

cs.CV2022

NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results

Yawei Li, Kai Zhang, Radu Timofte +108

This paper reviews the NTIRE 2022 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The task of the challenge was to super-reso…

cs.CV20217 cited

Spectrum-to-Kernel Translation for Accurate Blind Image Super-Resolution

Guangpin Tao, Xiaozhong Ji, Wenzhuo Wang +6

Deep-learning based Super-Resolution (SR) methods have exhibited promising performance under non-blind setting where blur kernel is known. However, blur kernels of Low-Resolution (…

cs.CV202118 cited

Learning Salient Boundary Feature for Anchor-free Temporal Action Localization

Chuming Lin, Chengming Xu, Donghao Luo +6

Temporal action localization is an important yet challenging task in video understanding. Typically, such a task aims at inferring both the action category and localization of the…

cs.CV2021

Learning Comprehensive Motion Representation for Action Recognition

Mingyu Wu, Boyuan Jiang, Donghao Luo +7

For action recognition learning, 2D CNN-based methods are efficient but may yield redundant features due to applying the same 2D convolution kernel to each frame. Recent efforts at…

cs.CV20207 cited

Temporal Distinct Representation Learning for Action Recognition

Junwu Weng, Donghao Luo, Yabiao Wang +6

Motivated by the previous success of Two-Dimensional Convolutional Neural Network (2D CNN) on image recognition, researchers endeavor to leverage it to characterize videos. However…