313 citations · 714 across the 53 of their papers we have counts for
9 papers · 1 filter
MSECNet: Accurate and Robust Normal Estimation for 3D Point Clouds by Multi-Scale Edge Conditioning
Haoyi Xiu, Xin Liu, Weimin Wang +2
Estimating surface normals from 3D point clouds is critical for various applications, including surface reconstruction and rendering. While existing methods for normal estimation p…
Multi-scale Promoted Self-adjusting Correlation Learning for Facial Action Unit Detection
Xin Liu, Kaishen Yuan, Xuesong Niu +4
Facial Action Unit (AU) detection is a crucial task in affective computing and social robotics as it helps to identify emotions expressed through facial expressions. Anatomically,…
Facial Affect Recognition based on Transformer Encoder and Audiovisual Fusion for the ABAW5 Challenge
Ziyang Zhang, Liuwei An, Zishun Cui +7
In this paper, we present our solutions for the 5th Workshop and Competition on Affective Behavior Analysis in-the-wild (ABAW), which includes four sub-challenges of Valence-Arousa…
NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results
Ren Yang, Radu Timofte, Meisong Zheng +75
This paper reviews the NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video. In this challenge, we proposed the LDV 2.0 dataset, which includes the…
Federated Remote Physiological Measurement with Imperfect Data
Xin Liu, Mingchuan Zhang, Ziheng Jiang +2
The growing need for technology that supports remote healthcare is being acutely highlighted by an aging population and the COVID-19 pandemic. In health-related machine learning ap…
DST: Data Selection and joint Training for Learning with Noisy Labels
Yi Wei, Xue Mei, Xin Liu +1
Training a deep neural network heavily relies on a large amount of training data with accurate annotations. To alleviate this problem, various methods have been proposed to annotat…
Generalized Image Reconstruction over T-Algebra
Liang Liao, Xuechun Zhang, Xinqiang Wang +2
Principal Component Analysis (PCA) is well known for its capability of dimension reduction and data compression. However, when using PCA for compressing/reconstructing images, imag…
AIM 2020 Challenge on Learned Image Signal Processing Pipeline
Andrey Ignatov, Radu Timofte, Zhilu Zhang +36
This paper reviews the second AIM learned ISP challenge and provides the description of the proposed solutions and results. The participating teams were solving a real-world RAW-to…
ENAS4D: Efficient Multi-stage CNN Architecture Search for Dynamic Inference
Zhihang Yuan, Xin Liu, Bingzhe Wu +1
Dynamic inference is a feasible way to reduce the computational cost of convolutional neural network(CNN), which can dynamically adjust the computation for each input sample. One o…