no code implementations • 30 Apr 2024 • Yao Gao, Qi Jiang, Shaohua Gao, Lei Sun, Kailun Yang, Kaiwei Wang
In this work, we present Global Search Optics (GSO) to automatically design compact computational imaging systems through two parts: (i) Fused Optimization Method for Automatic Optical Design (OptiFusion), which searches for diverse initial optical systems under certain design specifications; and (ii) Efficient Physic-aware Joint Optimization (EPJO), which conducts parallel joint optimization of initial optical systems and image reconstruction networks with the consideration of physical constraints, culminating in the selection of the optimal solution.
1 code implementation • 15 Mar 2024 • Qi Jiang, Zhonghua Yi, Shaohua Gao, Yao Gao, Xiaolong Qian, Hao Shi, Lei Sun, Zhijie Xu, Kailun Yang, Kaiwei Wang
Relying on paired synthetic data, existing learning-based Computational Aberration Correction (CAC) methods are confronted with the intricate and multifaceted synthetic-to-real domain gap, which leads to suboptimal performance in real-world applications.
1 code implementation • 22 Jun 2023 • Qi Jiang, Shaohua Gao, Yao Gao, Kailun Yang, Zhonghua Yi, Hao Shi, Lei Sun, Kaiwei Wang
In this paper, we propose a Panoramic Computational Imaging Engine (PCIE) to address minimalist and high-quality panoramic imaging.
no code implementations • 10 Mar 2023 • Xiuxiu Bai, Shuaishuai Zhao, Yao Gao, Zhe Liu
We verify this theory through simulation experiments and demonstrate the mode-locking pattern in real-world scene models.
no code implementations • 20 May 2022 • Xiuxiu Bai, Zhe Liu, Yao Gao, Bin Liu, Yongqiang Hao
Artificial neural networks have realized incredible successes at image recognition, but the underlying mechanism of visual space representation remains a huge mystery.
no code implementations • 23 Jul 2021 • Pinzhuo Tian, Yao Gao
However, most meta-learning literature focuses on dealing with tasks from a same domain, making it brittle to generalize to tasks from the other unseen domains.
no code implementations • 21 Apr 2021 • Zhong-Qiu Zhao, Yao Gao, Yuchen Ge, Weidong Tian
Experimental results on COCO and OCHuman keypoints datasets show that our proposed ODKD can improve the performance of different lightweight models by a large margin, and HRNet-W16 equipped with ODKD achieves state-of-the-art performance for lightweight human pose estimation.