Search Results for author: Minghao Guo

Found 10 papers, 6 papers with code

Polygrammar: Grammar for Digital Polymer Representation and Generation

no code implementations5 May 2021 Minghao Guo, Wan Shou, Liane Makatura, Timothy Erps, Michael Foshey, Wojciech Matusik

Here, we present a parametric, context-sensitive grammar designed specifically for the representation and generation of polymers.

Towards Evaluating and Training Verifiably Robust Neural Networks

1 code implementation CVPR 2021 Zhaoyang Lyu, Minghao Guo, Tong Wu, Guodong Xu, Kehuan Zhang, Dahua Lin

Recent works have shown that interval bound propagation (IBP) can be used to train verifiably robust neural networks.

Texture Memory-Augmented Deep Patch-Based Image Inpainting

1 code implementation28 Sep 2020 Rui Xu, Minghao Guo, Jiaqi Wang, Xiaoxiao Li, Bolei Zhou, Chen Change Loy

By bringing together the best of both paradigms, we propose a new deep inpainting framework where texture generation is guided by a texture memory of patch samples extracted from unmasked regions.

Image Inpainting Texture Synthesis

AM-LFS: AutoML for Loss Function Search

1 code implementation ICCV 2019 Chuming Li, Yuan Xin, Chen Lin, Minghao Guo, Wei Wu, Wanli Ouyang, Junjie Yan

The key contribution of this work is the design of search space which can guarantee the generalization and transferability on different vision tasks by including a bunch of existing prevailing loss functions in a unified formulation.

AutoML

See the World through Network Cameras

no code implementations14 Apr 2019 Yung-Hsiang Lu, George K. Thiruvathukal, Ahmed S. Kaseb, Kent Gauen, Damini Rijhwani, Ryan Dailey, Deeptanshu Malik, Yutong Huang, Sarah Aghajanzadeh, Minghao Guo

This paper describes the real-time data available from worldwide network cameras and potential applications.

IRLAS: Inverse Reinforcement Learning for Architecture Search

1 code implementation CVPR 2019 Minghao Guo, Zhao Zhong, Wei Wu, Dahua Lin, Junjie Yan

Motivated by the fact that human-designed networks are elegant in topology with a fast inference speed, we propose a mirror stimuli function inspired by biological cognition theory to extract the abstract topological knowledge of an expert human-design network (ResNeXt).

Neural Architecture Search

Dual-Agent Deep Reinforcement Learning for Deformable Face Tracking

no code implementations ECCV 2018 Minghao Guo, Jiwen Lu, Jie zhou

In this paper, we propose a dual-agent deep reinforcement learning (DADRL) method for deformable face tracking, which generates bounding boxes and detects facial landmarks interactively from face videos.

Facial Landmark Detection

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