199 citations · 456 across the 23 of their papers we have counts for
23 papers
Mutual Guidance and Residual Integration for Image Enhancement
Kun Zhou, KenKun Liu, Wenbo Li +2
Previous studies show the necessity of global and local adjustment for image enhancement. However, existing convolutional neural networks (CNNs) and transformer-based models face g…
Video Frame Interpolation with Transformer
Liying Lu, Ruizheng Wu, Huaijia Lin +2
Video frame interpolation (VFI), which aims to synthesize intermediate frames of a video, has made remarkable progress with development of deep convolutional networks over past yea…
Exploring Motion Ambiguity and Alignment for High-Quality Video Frame Interpolation
Kun Zhou, Wenbo Li, Xiaoguang Han +1
For video frame interpolation (VFI), existing deep-learning-based approaches strongly rely on the ground-truth (GT) intermediate frames, which sometimes ignore the non-unique natur…
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…