199 citations · 456 across the 23 of their papers we have counts for
7 papers · 1 filter
On Efficient Transformer-Based Image Pre-training for Low-Level Vision
Wenbo Li, Xin Lu, Shengju Qian +3
Pre-training has marked numerous state of the arts in high-level computer vision, while few attempts have ever been made to investigate how pre-training acts in image processing sy…
NLP Research and Resources at DaSciM, Ecole Polytechnique
Hadi Abdine, Yanzhu Guo, Moussa Kamal Eddine +5
DaSciM (Data Science and Mining) part of LIX at Ecole Polytechnique, established in 2013 and since then producing research results in the area of large scale data analysis via meth…
Sparse Steerable Convolutions: An Efficient Learning of SE(3)-Equivariant Features for Estimation and Tracking of Object Poses in 3D Space
Jiehong Lin, Hongyang Li, Ke Chen +2
As a basic component of SE(3)-equivariant deep feature learning, steerable convolution has recently demonstrated its advantages for 3D semantic analysis. The advantages are, howeve…
MASA-SR: Matching Acceleration and Spatial Adaptation for Reference-Based Image Super-Resolution
Liying Lu, Wenbo Li, Xin Tao +2
Reference-based image super-resolution (RefSR) has shown promising success in recovering high-frequency details by utilizing an external reference image (Ref). In this task, textur…
LAPAR: Linearly-Assembled Pixel-Adaptive Regression Network for Single Image Super-Resolution and Beyond
Wenbo Li, Kun Zhou, Lu Qi +3
Single image super-resolution (SISR) deals with a fundamental problem of upsampling a low-resolution (LR) image to its high-resolution (HR) version. Last few years have witnessed i…
Best-Buddy GANs for Highly Detailed Image Super-Resolution
Wenbo Li, Kun Zhou, Lu Qi +4
We consider the single image super-resolution (SISR) problem, where a high-resolution (HR) image is generated based on a low-resolution (LR) input. Recently, generative adversarial…