no code implementations • 19 Mar 2024 • Shen Zheng, Anurag Ghosh, Srinivasa G. Narasimhan
Discovering that shifting the source scale distribution improves backbone features, we developed a instance-level warping guidance aimed at object region sampling to mitigate source scale bias in domain adaptation.
1 code implementation • 1 Nov 2023 • Shen Zheng, Changjie Lu, Srinivasa G. Narasimhan
We first introduce a Triangular Probability Similarity (TPS) constraint to guide the generated images toward clear and rainy images in the discriminator manifold, thereby minimizing artifacts and distortions during rain generation.
1 code implementation • 28 Sep 2023 • Shen Zheng, Yuyu Zhang, Yijie Zhu, Chenguang Xi, Pengyang Gao, Xun Zhou, Kevin Chen-Chuan Chang
With the rapid advancement of large language models (LLMs), there is a pressing need for a comprehensive evaluation suite to assess their capabilities and limitations.
1 code implementation • 22 May 2023 • Hanyin Shao, Jie Huang, Shen Zheng, Kevin Chen-Chuan Chang
The advancement of large language models (LLMs) brings notable improvements across various applications, while simultaneously raising concerns about potential private data exposure.
no code implementations • 20 Apr 2023 • Shen Zheng, Jie Huang, Kevin Chen-Chuan Chang
To better understand the model's particular weaknesses in providing truthful answers, we embark an in-depth exploration of open-domain question answering.
1 code implementation • 21 Dec 2022 • Shen Zheng, Yiling Ma, Jinqian Pan, Changjie Lu, Gaurav Gupta
This paper presents a comprehensive survey of low-light image and video enhancement, addressing two primary challenges in the field.
1 code implementation • 13 Jul 2022 • Shen Zheng, Jinqian Pan, Changjie Lu, Gaurav Gupta
Point cloud analysis is challenging due to the irregularity of the point cloud data structure.
1 code implementation • 28 Jun 2022 • Changjie Lu, Shen Zheng, ZiRui Wang, Omar Dib, Gaurav Gupta
However, due to the unavailability of an effective metric to evaluate the difference between the real and the fake images, the posterior collapse and the vanishing gradient problem still exist, reducing the fidelity of the synthesized images.
1 code implementation • 20 Apr 2022 • Changjie Lu, Shen Zheng, Gaurav Gupta
This paper introduces UDA-VAE++, an unsupervised domain adaptation framework for cardiac segmentation with a compact loss function lower bound.
no code implementations • 26 Nov 2021 • Changjie Lu, Shen Zheng, Hailu Qiu
Fourth, we apply ordinary differential equations to examine AGH numbers at the different natural growthrate and reaction speed and output the potential propagation coefficient.
1 code implementation • 17 Nov 2021 • Shen Zheng, Changjie Lu, Yuxiong Wu, Gaurav Gupta
To address this issue, in this paper, we present a segmentation-aware progressive network (SAPNet) based upon contrastive learning for single image deraining.
1 code implementation • 3 Oct 2021 • Shen Zheng, Gaurav Gupta
Firstly, we design an enhancement factor extraction network using depthwise separable convolution for an efficient estimate of the pixel-wise light deficiency of an low-light image.
no code implementations • 12 Feb 2021 • Kanya Mo, Shen Zheng, Xiwei Wang, Jinghua Wang, Klaus-Dieter Schewe
The fully connected (FC) layer, one of the most fundamental modules in artificial neural networks (ANN), is often considered difficult and inefficient to train due to issues including the risk of overfitting caused by its large amount of parameters.
no code implementations • 14 Dec 2018 • Cheng Bian, Xin Yang, Jianqiang Ma, Shen Zheng, Yu-An Liu, Reza Nezafat, Pheng-Ann Heng, Yefeng Zheng
Accurately segmenting left atrium in MR volume can benefit the ablation procedure of atrial fibrillation.