38 citations · 46 across the 4 of their papers we have counts for
7 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…
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…
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…
HEMlets PoSh: Learning Part-Centric Heatmap Triplets for 3D Human Pose and Shape Estimation
Kun Zhou, Xiaoguang Han, Nianjuan Jiang +2
Estimating 3D human pose from a single image is a challenging task. This work attempts to address the uncertainty of lifting the detected 2D joints to the 3D space by introducing a…
HEMlets Pose: Learning Part-Centric Heatmap Triplets for Accurate 3D Human Pose Estimation
Kun Zhou, Xiaoguang Han, Nianjuan Jiang +2
Estimating 3D human pose from a single image is a challenging task. This work attempts to address the uncertainty of lifting the detected 2D joints to the 3D space by introducing a…
Adversarial 3D Human Pose Estimation via Multimodal Depth Supervision
Kun Zhou, Jinmiao Cai, Yao Li +5
In this paper, a novel deep-learning based framework is proposed to infer 3D human poses from a single image. Specifically, a two-phase approach is developed. We firstly utilize a…