1 code implementation • 27 Oct 2023 • Xiaokai Zhang, Na Zhu, Yiming He, Jia Zou, Qike Huang, Xiaoxiao Jin, Yanjun Guo, Chenyang Mao, Yang Li, Zhe Zhu, Dengfeng Yue, Fangzhen Zhu, Yifan Wang, Yiwen Huang, Runan Wang, Cheng Qin, Zhenbing Zeng, Shaorong Xie, Xiangfeng Luo, Tuo Leng
In this paper, we have constructed a consistent formal plane geometry system.
no code implementations • 22 May 2023 • Yiwen Huang, Zhiqiu Yu, Xinjie Yi, Yue Wang, James Tompkin
This results in a new model that effectively removes the quality tax between 3DMM conditioned face GANs and the unconditional StyleGAN.
no code implementations • ICCV 2023 • Jinglun Li, Xinyu Zhou, Pinxue Guo, Yixuan Sun, Yiwen Huang, Weifeng Ge, Wenqiang Zhang
We use one fold as the in-distribution dataset and the others as out-of-distribution datasets to evaluate the proposed method.
1 code implementation • CVPR 2023 • Yixuan Sun, Dongyang Zhao, Zhangyue Yin, Yiwen Huang, Tao Gui, Wenqiang Zhang, Weifeng Ge
The asymmetric feature learning module exploits a biased cross-attention mechanism to encode token features of source images with their target counterparts.
1 code implementation • ICCV 2023 • Yiwen Huang, Yixuan Sun, Chenghang Lai, Qing Xu, Xiaomei Wang, Xuli Shen, Weifeng Ge
Following the spirit of multiple instance learning (MIL), we decompose the weakly supervised correspondence learning problem into three stages: image-level matching, region-level matching, and pixel-level matching.
1 code implementation • CVPR 2023 • Yixuan Sun, Yiwen Huang, Haijing Guo, Yuzhou Zhao, Runmin Wu, Yizhou Yu, Weifeng Ge, Wenqiang Zhang
Semantic correspondence have built up a new way for object recognition.
no code implementations • MM '22: Proceedings of the 30th ACM International Conference on Multimedia 2022 • Yan Wang, Yixuan Sun, Wei Song, Shuyong Gao, Yiwen Huang, Zhaoyu Chen, Weifeng Ge, and Wenqiang Zhang
To obtain consistent prediction probabilities from the dual path, we further propose a dual path regularization loss, aiming to minimize the divergence between the distributions of two-path embeddings.
Ranked #13 on Dynamic Facial Expression Recognition on DFEW
Dynamic Facial Expression Recognition Representation Learning
no code implementations • CVPR 2022 • Yan Wang, Yixuan Sun, Yiwen Huang, Zhongying Liu, Shuyong Gao, Wei zhang, Weifeng Ge, Wenqiang Zhang
Current benchmarks for facial expression recognition (FER) mainly focus on static images, while there are limited datasets for FER in videos.
no code implementations • 20 Nov 2019 • Gabriele Vajente, Yiwen Huang, Maximiliano Isi, Jenne C. Driggers, Jeffrey S. Kissel, Marek J. Szczepanczyk, Salvatore Vitale
Signal extraction out of background noise is a common challenge in high precision physics experiments, where the measurement output is often a continuous data stream.
1 code implementation • 22 Apr 2019 • Lluís Galbany, Chris Ashall, Peter Hoeflich, Santiago González-Gaitán, Stefan Taubenberger, Maximilian Stritzinger, Eric Y. Hsiao, Paolo Mazzali, Eddie Baron, Stéphane Blondin, Subhash Bose, Mattia Bulla, Jamison F. Burke, Christopher R. Burns, Régis Cartier, Ping Chen, Massimo Della Valle, Tiara R. Diamond, Claudia P. Gutiérrez, Jussi Harmanen, Daichi Hiramatsu, T. W. -S. Holoien, Griffin Hosseinzadeh, D. Andrew Howell, Yiwen Huang, Cosimo Inserra, Thomas de Jaeger, Saurabh W. Jha, Tuomas Kangas, Markus Kromer, Joseph D. Lyman, Kate Maguire, George Howie Marion, Dan Milisavljevic, Simon J. Prentice, Alessandro Razza, Thomas M. Reynolds, David J. Sand, Benjamin J. Shappee, Rohit Shekhar, Stephen J. Smartt, Keivan G. Stassun, Mark Sullivan, Stefano Valenti, Steven Villanueva, Xiao-Feng Wang, J. Craig Wheeler, Qian Zhai, Jujia Zhang
Our modeling suggests that the narrow [Ca II] features observed in the nebular spectrum are associated with $^{48}$Ca from electron capture during the explosion, which is expected to occur only in white dwarfs that explode near or at the $M_{\rm Ch}$ limit.
Solar and Stellar Astrophysics High Energy Astrophysical Phenomena
1 code implementation • 27 Nov 2018 • Yiwen Huang, Rihui Wu, Pinglai Ou, Ziyong Feng
We thus exploit the aggregation nature of shortcut connections at a finer architectural level and place them within wide convolutional layers.
no code implementations • 16 Apr 2018 • Yiwen Huang, Ming Qin
Deep convolutional neural networks (DCNN) have been widely adopted for research on super resolution recently, however previous work focused mainly on stacking as many layers as possible in their model, in this paper, we present a new perspective regarding to image restoration problems that we can construct the neural network model reflecting the physical significance of the image restoration process, that is, embedding the a priori knowledge of image restoration directly into the structure of our neural network model, we employed a symmetric non-linear colorspace, the sigmoidal transfer, to replace traditional transfers such as, sRGB, Rec. 709, which are asymmetric non-linear colorspaces, we also propose a "reuse plus patch" method to deal with super resolution of different scaling factors, our proposed methods and model show generally superior performance over previous work even though our model was only roughly trained and could still be underfitting the training set.
no code implementations • 27 Jul 2016 • Ilia Vovsha, Ansaf Salleb-Aouissi, Anita Raja, Thomas Koch, Alex Rybchuk, Axinia Radeva, Ashwath Rajan, Yiwen Huang, Hatim Diab, Ashish Tomar, Ronald Wapner
We describe an application of machine learning to the problem of predicting preterm birth.