63 citations · 150 across the 10 of their papers we have counts for
6 papers · 1 filter
3D Face Arbitrary Style Transfer
Xiangwen Deng, Yingshuang Zou, Yuanhao Cai +6
Style transfer of 3D faces has gained more and more attention. However, previous methods mainly use images of artistic faces for style transfer while ignoring arbitrary style image…
Retinexformer: One-stage Retinex-based Transformer for Low-light Image Enhancement
Yuanhao Cai, Hao Bian, Jing Lin +3
When enhancing low-light images, many deep learning algorithms are based on the Retinex theory. However, the Retinex model does not consider the corruptions hidden in the dark or i…
Unsupervised Flow-Aligned Sequence-to-Sequence Learning for Video Restoration
Jing Lin, Xiaowan Hu, Yuanhao Cai +5
How to properly model the inter-frame relation within the video sequence is an important but unsolved challenge for video restoration (VR). In this work, we propose an unsupervised…
MST++: Multi-stage Spectral-wise Transformer for Efficient Spectral Reconstruction
Yuanhao Cai, Jing Lin, Zudi Lin +5
Existing leading methods for spectral reconstruction (SR) focus on designing deeper or wider convolutional neural networks (CNNs) to learn the end-to-end mapping from the RGB image…
Learning to Generate Realistic Noisy Images via Pixel-level Noise-aware Adversarial Training
Yuanhao Cai, Xiaowan Hu, Haoqian Wang +3
Existing deep learning real denoising methods require a large amount of noisy-clean image pairs for supervision. Nonetheless, capturing a real noisy-clean dataset is an unacceptabl…
Efficient Human Pose Estimation by Learning Deeply Aggregated Representations
Zhengxiong Luo, Zhicheng Wang, Yuanhao Cai +6
In this paper, we propose an efficient human pose estimation network (DANet) by learning deeply aggregated representations. Most existing models explore multi-scale information mai…