Search Results for author: Yao Gao

Found 6 papers, 1 papers with code

Real-World Computational Aberration Correction via Quantized Domain-Mixing Representation

no code implementations15 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.

Unsupervised Domain Adaptation

Minimalist and High-Quality Panoramic Imaging with PSF-aware Transformers

1 code implementation22 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.

Super-Resolution

Mode-locking Theory for Long-Range Interaction in Artificial Neural Networks

no code implementations10 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.

Emergence of Double-slit Interference by Representing Visual Space in Artificial Neural Networks

no code implementations20 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.

Improving the Generalization of Meta-learning on Unseen Domains via Adversarial Shift

no code implementations23 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.

Cross-Domain Few-Shot Domain Generalization +1

Orderly Dual-Teacher Knowledge Distillation for Lightweight Human Pose Estimation

no code implementations21 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.

Binarization Knowledge Distillation +2

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