1 code implementation • 14 Dec 2023 • Ziteng Cui, Lin Gu, Xiao Sun, Xianzheng Ma, Yu Qiao, Tatsuya Harada
The standard Neural Radiance Fields (NeRF) paradigm employs a viewer-centered methodology, entangling the aspects of illumination and material reflectance into emission solely from 3D points.
1 code implementation • 10 Mar 2023 • Ziteng Cui, Lin Gu, Xiao Sun, Xianzheng Ma, Yu Qiao, Tatsuya Harada
Common capture low-light scenes are challenging for most computer vision techniques, including Neural Radiance Fields (NeRF).
1 code implementation • 31 Oct 2022 • Ruichen Yao, Ziteng Cui, Xiaoxiao Li, Lin Gu
Fairness is a fundamental requirement for trustworthy and human-centered Artificial Intelligence (AI) system.
1 code implementation • 5 Aug 2022 • Ziteng Cui, Yingying Zhu, Lin Gu, Guo-Jun Qi, Xiaoxiao Li, Renrui Zhang, Zenghui Zhang, Tatsuya Harada
Image restoration algorithms such as super resolution (SR) are indispensable pre-processing modules for object detection in low quality images.
1 code implementation • 30 May 2022 • Ziteng Cui, Kunchang Li, Lin Gu, Shenghan Su, Peng Gao, Zhengkai Jiang, Yu Qiao, Tatsuya Harada
Challenging illumination conditions (low-light, under-exposure and over-exposure) in the real world not only cast an unpleasant visual appearance but also taint the computer vision tasks.
Ranked #2 on Image Enhancement on Exposure-Errors
2 code implementations • ICCV 2021 • Ziteng Cui, Guo-Jun Qi, Lin Gu, ShaoDi You, Zenghui Zhang, Tatsuya Harada
To enhance object detection in a dark environment, we propose a novel multitask auto encoding transformation (MAET) model which is able to explore the intrinsic pattern behind illumination translation.
Ranked #1 on 2D Object Detection on ExDark
no code implementations • 14 Apr 2022 • Shenghan Su, Ziteng Cui, Weiwei Guo, Zenghui Zhang, Wenxian Yu
Deep learning methods exhibit outstanding performance in synthetic aperture radar (SAR) image interpretation tasks.
1 code implementation • ICCV 2023 • Renrui Zhang, Han Qiu, Tai Wang, Ziyu Guo, Xuanzhuo Xu, Ziteng Cui, Yu Qiao, Peng Gao, Hongsheng Li
In this paper, we introduce the first DETR framework for Monocular DEtection with a depth-guided TRansformer, named MonoDETR.
3D Object Detection From Monocular Images Autonomous Driving +4
no code implementations • 22 Jan 2022 • Keqi Wang, Ziteng Cui, Jieru Jia, Hao Xu, Ge Wu, Yin Zhuang, Lu Chen, Zhiguo Hu, Yuhua Qian
However, the convolution operation is based on a local sliding window mechanism, which is difficult to construct the long-range dependencies of the feature maps.
no code implementations • 7 Jan 2022 • Ziteng Cui, Yingying Zhu, Lin Gu, Guo-Jun Qi, Xiaoxiao Li, Peng Gao, Zenghui Zhang, Tatsuya Harada
Image restoration algorithms such as super resolution (SR) are indispensable pre-processing modules for object detection in degraded images.
1 code implementation • 7 Mar 2021 • Xiaoxiao Li, Ziteng Cui, Yifan Wu, Lin Gu, Tatsuya Harada
To tackle this issue, we propose an adversarial multi-task training strategy to simultaneously mitigate and detect bias in the deep learning-based medical image analysis system.