Search Results for author: Tao Yue

Found 10 papers, 3 papers with code

Adaptive and Cascaded Compressive Sensing

no code implementations21 Mar 2022 Chenxi Qiu, Tao Yue, Xuemei Hu

Scene-dependent adaptive compressive sensing (CS) has been a long pursuing goal which has huge potential in significantly improving the performance of CS.

Compressive Sensing

Fisher Information Guidance for Learned Time-of-Flight Imaging

no code implementations CVPR 2022 Jiaqu Li, Tao Yue, Sijie Zhao, Xuemei Hu

Indirect Time-of-Flight (ToF) imaging is widely applied in practice for its superiorities on cost and spatial resolution.

Prediction Surface Uncertainty Quantification in Object Detection Models for Autonomous Driving

1 code implementation11 Jul 2021 Ferhat Ozgur Catak, Tao Yue, Shaukat Ali

Object detection in autonomous cars is commonly based on camera images and Lidar inputs, which are often used to train prediction models such as deep artificial neural networks for decision making for object recognition, adjusting speed, etc.

Autonomous Driving Decision Making +3

Distribution-Aware Adaptive Multi-Bit Quantization

no code implementations CVPR 2021 Sijie Zhao, Tao Yue, Xuemei Hu

In this paper, we explore the compression of deep neural networks by quantizing the weights and activations into multi-bit binary networks (MBNs).

Image Classification Quantization

Controlling the Rain: From Removal to Rendering

no code implementations CVPR 2021 Siqi Ni, Xueyun Cao, Tao Yue, Xuemei Hu

Existing rain image editing methods focus on either removing rain from rain images or rendering rain on rain-free images.

Continuous Control Rain Removal

Deep Image Compression via End-to-End Learning

1 code implementation5 Jun 2018 Haojie Liu, Tong Chen, Qiu Shen, Tao Yue, Zhan Ma

We present a lossy image compression method based on deep convolutional neural networks (CNNs), which outperforms the existing BPG, WebP, JPEG2000 and JPEG as measured via multi-scale structural similarity (MS-SSIM), at the same bit rate.

Image Compression MS-SSIM +3

Multispectral Image Intrinsic Decomposition via Subspace Constraint

no code implementations CVPR 2018 Qian Huang, Weixin Zhu, Yang Zhao, Linsen Chen, Yao Wang, Tao Yue, Xun Cao

In this paper, a new Multispectral Image Intrinsic Decomposition model (MIID) is presented to decompose the shading and reflectance from a single multispectral image.

Multispectral Image Intrinsic Decomposition via Low Rank Constraint

no code implementations24 Feb 2018 Qian Huang, Weixin Zhu, Yang Zhao, Linsen Chen, Yao Wang, Tao Yue, Xun Cao

In this paper, a Low Rank Multispectral Image Intrinsic Decomposition model (LRIID) is presented to decompose the shading and reflectance from a single multispectral image.

Blind Optical Aberration Correction by Exploring Geometric and Visual Priors

no code implementations CVPR 2015 Tao Yue, Jinli Suo, Jue Wang, Xun Cao, Qionghai Dai

Furthermore, by investigating the visual artifacts of aberration degenerated images captured by consumer-level cameras, the non-uniform distribution of sharpness across color channels and the image lattice is exploited as visual priors, resulting in a novel strategy to utilize the guidance from the sharpest channel and local image regions to improve the overall performance and robustness.

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