no code implementations • 27 Feb 2024 • Ling Yang, Haotian Qian, Zhilong Zhang, Jingwei Liu, Bin Cui
In this pioneering approach, we compel the model to learn manifold structures between samples in each training batch.
1 code implementation • 26 Feb 2024 • Ling Yang, Zhilong Zhang, Zhaochen Yu, Jingwei Liu, Minkai Xu, Stefano Ermon, Bin Cui
To address this issue, we propose a novel and general contextualized diffusion model (ContextDiff) by incorporating the cross-modal context encompassing interactions and alignments between text condition and visual sample into forward and reverse processes.
no code implementations • NeurIPS 2023 • Ling Yang, Jingwei Liu, Shenda Hong, Zhilong Zhang, Zhilin Huang, Zheming Cai, Wentao Zhang, Bin Cui
In this way, each point can better reconstruct itself by preserving its semantic connections with neighborhood context.
Ranked #1 on Image Inpainting on CelebA (LPIPS metric)
no code implementations • 10 Aug 2023 • Xinyu Lyu, Jingwei Liu, Yuyu Guo, Lianli Gao
Long-temporal human actions supervise the model to generate multiple scene graphs that conform to the global constraints and avoid the model being unable to learn the tail predicates.
no code implementations • 11 Jun 2023 • Jingwei Liu
This paper gives a preliminary attempt at bridging FEP and machine learning, via a classical neural network model, the Helmholtz machine.
no code implementations • 6 Jun 2023 • Xiao Lin, Xiaokai Chen, Linfeng Song, Jingwei Liu, Biao Li, Peng Jiang
An accurate prediction of watch time has been of vital importance to enhance user engagement in video recommender systems.
no code implementations • 24 Sep 2022 • Haojie Xu, Weifeng Liu, Jingwei Liu, Mingzheng Li, Yu Feng, Yasi Peng, Yunwei Shi, Xiao Sun, Meng Wang
Our experiments demonstrate the effectiveness of our proposed model and hybrid fusion strategy on multimodal fusion, and the AUC of our proposed model on the test set is 0. 8972.
no code implementations • 21 May 2022 • Jingwei Liu
We first develop European power option pricing in two types of payoffs with martingale method under the market assumption that Vasic\v{e}k interest rate and exponential Ornstein-Uhlenbeck process are correlated in equivalent martingale measure probability space.
no code implementations • 29 Sep 2021 • Jingwei Liu, Yi Gu, Shentong Mo, Zhun Sun, Shumin Han, Jiafeng Guo, Xueqi Cheng
In self-supervised learning frameworks, deep networks are optimized to align different views of an instance that contains the similar visual semantic information.
no code implementations • 9 Jan 2021 • Jingwei Liu
For 3-class classification of China, the Top-1 accuracy rate can reach 82. 45\% (train 60\%, test=40\%); For 2-class classification of China, the Top-1 accuracy rate can reach 97. 35\% (train 80\%, test 20\%); For 6-class classification task of world, when the ratio of training set and test set is 20\% : 80\% , the Top-1 accuracy rate can achieve 30. 30\%.
1 code implementation • 16 Sep 2020 • Xuehui Yu, Zhenjun Han, Yuqi Gong, Nan Jiang, Jian Zhao, Qixiang Ye, Jie Chen, Yuan Feng, Bin Zhang, Xiaodi Wang, Ying Xin, Jingwei Liu, Mingyuan Mao, Sheng Xu, Baochang Zhang, Shumin Han, Cheng Gao, Wei Tang, Lizuo Jin, Mingbo Hong, Yuchao Yang, Shuiwang Li, Huan Luo, Qijun Zhao, Humphrey Shi
The 1st Tiny Object Detection (TOD) Challenge aims to encourage research in developing novel and accurate methods for tiny object detection in images which have wide views, with a current focus on tiny person detection.
no code implementations • 17 Nov 2019 • Ruoyu Guo, Cheng Cui, Yuning Du, Xianglong Meng, Xiaodi Wang, Jingwei Liu, Jianfeng Zhu, Yuan Feng, Shumin Han
We present an object detection framework based on PaddlePaddle.
no code implementations • 19 Apr 2019 • Jingwei Liu
Marker family genome sequences play important roles in describing specific microbial clades within species, a framework of support vector machine (SVM) based microbial species classification with N-best algorithm is constructed to classify the centroid marker genome fragments randomly generated from marker genome sequences on MetaRef.
no code implementations • 4 Sep 2016 • Yi Liu, Jingwei Liu
A calculation formula of volume of revolution with integration by parts of definite integral is derived based on monotone function, and extended to a general case that curved trapezoids is determined by continuous, piecewise strictly monotone and differential function.