Search Results for author: Boxin Shi

Found 53 papers, 17 papers with code

FHDe²Net: Full High Definition Demoireing Network

no code implementations ECCV 2020 Bin He, Ce Wang, Boxin Shi, Ling-Yu Duan

Frequency aliasing in the digital capture of display screens leads to the moir´e pattern, appearing as stripe-shaped distortions in images.

What is Learned in Deep Uncalibrated Photometric Stereo?

no code implementations ECCV 2020 Guan-Ying Chen, Michael Waechter, Boxin Shi, Kwan-Yee K. Wong, Yasuyuki Matsushita

Based on this insight, we propose a guided calibration network, named GCNet, that explicitly leverages object shape and shading information for improved lighting estimation.

Conditional Image Repainting via Semantic Bridge and Piecewise Value Function

no code implementations ECCV 2020 Shuchen Weng, Wenbo Li, Dawei Li, Hongxia Jin, Boxin Shi

We study conditional image repainting where a model is trained to generate visual content conditioned on user inputs, and composite the generated content seamlessly onto a user provided image while preserving the semantics of users' inputs.

1000x Faster Camera and Machine Vision with Ordinary Devices

no code implementations23 Jan 2022 Tiejun Huang, Yajing Zheng, Zhaofei Yu, Rui Chen, Yuan Li, Ruiqin Xiong, Lei Ma, Junwei Zhao, Siwei Dong, Lin Zhu, Jianing Li, Shanshan Jia, Yihua Fu, Boxin Shi, Si Wu, Yonghong Tian

By treating vidar as spike trains in biological vision, we have further developed a spiking neural network-based machine vision system that combines the speed of the machine and the mechanism of biological vision, achieving high-speed object detection and tracking 1, 000x faster than human vision.

Object Detection

Learning to dehaze with polarization

no code implementations NeurIPS 2021 Chu Zhou, Minggui Teng, Yufei Han, Chao Xu, Boxin Shi

Haze, a common kind of bad weather caused by atmospheric scattering, decreases the visibility of scenes and degenerates the performance of computer vision algorithms.

Image Dehazing Single Image Dehazing

Optical Flow Estimation for Spiking Camera

no code implementations8 Oct 2021 Liwen Hu, Rui Zhao, Ziluo Ding, Lei Ma, Boxin Shi, Ruiqin Xiong, Tiejun Huang

Further, for training SCFlow, we synthesize two sets of optical flow data for the spiking camera, SPIkingly Flying Things and Photo-realistic High-speed Motion, denoted as SPIFT and PHM respectively, corresponding to random high-speed and well-designed scenes.

Event-based vision Frame +2

Label Distribution Amendment with Emotional Semantic Correlations for Facial Expression Recognition

no code implementations23 Jul 2021 Shasha Mao, GuangHui Shi, Licheng Jiao, Shuiping Gou, Yangyang Li, Lin Xiong, Boxin Shi

Based on this, we propose a new method that amends the label distribution of each facial image by leveraging correlations among expressions in the semantic space.

Facial Expression Recognition

Panoramic Image Reflection Removal

no code implementations CVPR 2021 Yuchen Hong, Qian Zheng, Lingran Zhao, Xudong Jiang, Alex C. Kot, Boxin Shi

This paper studies the problem of panoramic image reflection removal, aiming at reliving the content ambiguity between reflection and transmission scenes.

Reflection Removal

EventZoom: Learning To Denoise and Super Resolve Neuromorphic Events

no code implementations CVPR 2021 Peiqi Duan, Zihao W. Wang, Xinyu Zhou, Yi Ma, Boxin Shi

EventZoom is trained in a noise-to-noise fashion where the two ends of the network are unfiltered noisy events, enforcing noise-free event restoration.

Denoising Image Reconstruction +1

Multispectral Photometric Stereo for Spatially-Varying Spectral Reflectances: A Well Posed Problem?

1 code implementation CVPR 2021 Heng Guo, Fumio Okura, Boxin Shi, Takuya Funatomi, Yasuhiro Mukaigawa, Yasuyuki Matsushita

To make the problem well-posed, existing MPS methods rely on restrictive assumptions, such as shape prior, surfaces having a monochromatic with uniform albedo.

Normal Integration via Inverse Plane Fitting With Minimum Point-to-Plane Distance

1 code implementation CVPR 2021 Xu Cao, Boxin Shi, Fumio Okura, Yasuyuki Matsushita

Experimental results on analytically computed, synthetic, and real-world surfaces show that our method yields accurate and stable reconstruction for both orthographic and perspective normal maps.

Surface Reconstruction

High-Speed Image Reconstruction Through Short-Term Plasticity for Spiking Cameras

no code implementations CVPR 2021 Yajing Zheng, Lingxiao Zheng, Zhaofei Yu, Boxin Shi, Yonghong Tian, Tiejun Huang

Mimicking the sampling mechanism of the fovea, a retina-inspired camera, named spiking camera, is developed to record the external information with a sampling rate of 40, 000 Hz, and outputs asynchronous binary spike streams.

Image Reconstruction

DeRenderNet: Intrinsic Image Decomposition of Urban Scenes with Shape-(In)dependent Shading Rendering

no code implementations28 Apr 2021 Yongjie Zhu, Jiajun Tang, Si Li, Boxin Shi

We propose DeRenderNet, a deep neural network to decompose the albedo and latent lighting, and render shape-(in)dependent shadings, given a single image of an outdoor urban scene, trained in a self-supervised manner.

Intrinsic Image Decomposition

Spatially-Varying Outdoor Lighting Estimation from Intrinsics

no code implementations CVPR 2021 Yongjie Zhu, yinda zhang, Si Li, Boxin Shi

We train a deep neural network to regress intrinsic cues with physically-based constraints and use them to conduct global and local lightings estimation.

EvIntSR-Net: Event Guided Multiple Latent Frames Reconstruction and Super-Resolution

no code implementations ICCV 2021 Jin Han, Yixin Yang, Chu Zhou, Chao Xu, Boxin Shi

To reconstruct high-resolution intensity images from event data, we propose EvIntSR-Net that converts event data to multiple latent intensity frames to achieve super-resolution on intensity images in this paper.

Frame Super-Resolution

GPS-Net: Graph-based Photometric Stereo Network

no code implementations NeurIPS 2020 Zhuokun Yao, Kun Li, Ying Fu, Haofeng Hu, Boxin Shi

For all-pixel operation, we propose the Normal Regression Network to make efficient use of the intra-image spatial information for predicting a surface normal map with rich details.

UnModNet: Learning to Unwrap a Modulo Image for High Dynamic Range Imaging

no code implementations NeurIPS 2020 Chu Zhou, Hang Zhao, Jin Han, Chang Xu, Chao Xu, Tiejun Huang, Boxin Shi

A conventional camera often suffers from over- or under-exposure when recording a real-world scene with a very high dynamic range (HDR).

Group Contextual Encoding for 3D Point Clouds

1 code implementation NeurIPS 2020 Xu Liu, Chengtao Li, Jian Wang, Jingbo Wang, Boxin Shi, Xiaodong He

In this work, we extended the contextual encoding layer that was originally designed for 2D tasks to 3D Point Cloud scenarios.

Scene Understanding

Deep Photometric Stereo for Non-Lambertian Surfaces

1 code implementation26 Jul 2020 Guan-Ying Chen, Kai Han, Boxin Shi, Yasuyuki Matsushita, Kwan-Yee K. Wong

To deal with the uncalibrated scenario where light directions are unknown, we introduce a new convolutional network, named LCNet, to estimate light directions from input images.

A Semi-Supervised Assessor of Neural Architectures

no code implementations CVPR 2020 Yehui Tang, Yunhe Wang, Yixing Xu, Hanting Chen, Chunjing Xu, Boxin Shi, Chao Xu, Qi Tian, Chang Xu

A graph convolutional neural network is introduced to predict the performance of architectures based on the learned representations and their relation modeled by the graph.

Neural Architecture Search

Distilling portable Generative Adversarial Networks for Image Translation

no code implementations7 Mar 2020 Hanting Chen, Yunhe Wang, Han Shu, Changyuan Wen, Chunjing Xu, Boxin Shi, Chao Xu, Chang Xu

To promote the capability of student generator, we include a student discriminator to measure the distances between real images, and images generated by student and teacher generators.

Image-to-Image Translation Knowledge Distillation +1

Beyond Dropout: Feature Map Distortion to Regularize Deep Neural Networks

2 code implementations23 Feb 2020 Yehui Tang, Yunhe Wang, Yixing Xu, Boxin Shi, Chao Xu, Chunjing Xu, Chang Xu

On one hand, massive trainable parameters significantly enhance the performance of these deep networks.

On Positive-Unlabeled Classification in GAN

1 code implementation CVPR 2020 Tianyu Guo, Chang Xu, Jiajun Huang, Yunhe Wang, Boxin Shi, Chao Xu, DaCheng Tao

In contrast, it is more reasonable to treat the generated data as unlabeled, which could be positive or negative according to their quality.

Classification General Classification

Multi-View Photometric Stereo: A Robust Solution and Benchmark Dataset for Spatially Varying Isotropic Materials

no code implementations18 Jan 2020 Min Li, Zhenglong Zhou, Zhe Wu, Boxin Shi, Changyu Diao, Ping Tan

From a single viewpoint, we use a set of photometric stereo images to identify surface points with the same distance to the camera.

AdderNet: Do We Really Need Multiplications in Deep Learning?

2 code implementations CVPR 2020 Hanting Chen, Yunhe Wang, Chunjing Xu, Boxin Shi, Chao Xu, Qi Tian, Chang Xu

The widely-used convolutions in deep neural networks are exactly cross-correlation to measure the similarity between input feature and convolution filters, which involves massive multiplications between float values.

Learning from Bad Data via Generation

no code implementations NeurIPS 2019 Tianyu Guo, Chang Xu, Boxin Shi, Chao Xu, DaCheng Tao

A worst-case formulation can be developed over this distribution set, and then be interpreted as a generation task in an adversarial manner.

Reflection Separation using a Pair of Unpolarized and Polarized Images

1 code implementation NeurIPS 2019 Youwei Lyu, Zhaopeng Cui, Si Li, Marc Pollefeys, Boxin Shi

When we take photos through glass windows or doors, the transmitted background scene is often blended with undesirable reflection.

DIST: Rendering Deep Implicit Signed Distance Function with Differentiable Sphere Tracing

1 code implementation CVPR 2020 Shaohui Liu, yinda zhang, Songyou Peng, Boxin Shi, Marc Pollefeys, Zhaopeng Cui

We propose a differentiable sphere tracing algorithm to bridge the gap between inverse graphics methods and the recently proposed deep learning based implicit signed distance function.

CARS: Continuous Evolution for Efficient Neural Architecture Search

1 code implementation CVPR 2020 Zhaohui Yang, Yunhe Wang, Xinghao Chen, Boxin Shi, Chao Xu, Chunjing Xu, Qi Tian, Chang Xu

Architectures in the population that share parameters within one SuperNet in the latest generation will be tuned over the training dataset with a few epochs.

Neural Architecture Search

Hyperspectral City V1.0 Dataset and Benchmark

no code implementations24 Jul 2019 Shaodi You, Erqi Huang, Shuaizhe Liang, Yongrong Zheng, Yunxiang Li, Fan Wang, Sen Lin, Qiu Shen, Xun Cao, Diming Zhang, Yuanjiang Li, Yu Li, Ying Fu, Boxin Shi, Feng Lu, Yinqiang Zheng, Robby T. Tan

This document introduces the background and the usage of the Hyperspectral City Dataset and the benchmark.

Bringing Giant Neural Networks Down to Earth with Unlabeled Data

no code implementations13 Jul 2019 Yehui Tang, Shan You, Chang Xu, Boxin Shi, Chao Xu

Specifically, we exploit the unlabeled data to mimic the classification characteristics of giant networks, so that the original capacity can be preserved nicely.

SPLINE-Net: Sparse Photometric Stereo through Lighting Interpolation and Normal Estimation Networks

no code implementations ICCV 2019 Qian Zheng, Yiming Jia, Boxin Shi, Xudong Jiang, Ling-Yu Duan, Alex C. Kot

This paper solves the Sparse Photometric stereo through Lighting Interpolation and Normal Estimation using a generative Network (SPLINE-Net).

Data-Free Learning of Student Networks

3 code implementations ICCV 2019 Hanting Chen, Yunhe Wang, Chang Xu, Zhaohui Yang, Chuanjian Liu, Boxin Shi, Chunjing Xu, Chao Xu, Qi Tian

Learning portable neural networks is very essential for computer vision for the purpose that pre-trained heavy deep models can be well applied on edge devices such as mobile phones and micro sensors.

Neural Network Compression

Deep Shape from Polarization

no code implementations ECCV 2020 Yunhao Ba, Alex Ross Gilbert, Franklin Wang, Jinfa Yang, Rui Chen, Yiqin Wang, Lei Yan, Boxin Shi, Achuta Kadambi

This paper makes a first attempt to bring the Shape from Polarization (SfP) problem to the realm of deep learning.

Self-calibrating Deep Photometric Stereo Networks

1 code implementation CVPR 2019 Guan-Ying Chen, Kai Han, Boxin Shi, Yasuyuki Matsushita, Kwan-Yee K. Wong

This paper proposes an uncalibrated photometric stereo method for non-Lambertian scenes based on deep learning.

Face Image Reflection Removal

no code implementations3 Mar 2019 Renjie Wan, Boxin Shi, Haoliang Li, Ling-Yu Duan, Alex C. Kot

Face images captured through the glass are usually contaminated by reflections.

Face Recognition Reflection Removal

Event-driven Video Frame Synthesis

1 code implementation26 Feb 2019 Zihao W. Wang, Weixin Jiang, Kuan He, Boxin Shi, Aggelos Katsaggelos, Oliver Cossairt

Temporal Video Frame Synthesis (TVFS) aims at synthesizing novel frames at timestamps different from existing frames, which has wide applications in video codec, editing and analysis.

Deblurring Denoising +3

Robust Student Network Learning

no code implementations30 Jul 2018 Tianyu Guo, Chang Xu, Shiyi He, Boxin Shi, Chao Xu, DaCheng Tao

In this way, a portable student network with significantly fewer parameters can achieve a considerable accuracy which is comparable to that of teacher network.

Depth-Aware Stereo Video Retargeting

no code implementations CVPR 2018 Bing Li, Chia-Wen Lin, Boxin Shi, Tiejun Huang, Wen Gao, C. -C. Jay Kuo

As compared with traditional video retargeting, stereo video retargeting poses new challenges because stereo video contains the depth information of salient objects and its time dynamics.

Uncalibrated Photometric Stereo Under Natural Illumination

no code implementations CVPR 2018 Zhipeng Mo, Boxin Shi, Feng Lu, Sai-Kit Yeung, Yasuyuki Matsushita

This paper presents a photometric stereo method that works with unknown natural illuminations without any calibration object.

CRRN: Multi-Scale Guided Concurrent Reflection Removal Network

1 code implementation CVPR 2018 Renjie Wan, Boxin Shi, Ling-Yu Duan, Ah-Hwee Tan, Alex C. Kot

Removing the undesired reflections from images taken through the glass is of broad application to various computer vision tasks.

Reflection Removal

Benchmarking Single-Image Reflection Removal Algorithms

no code implementations ICCV 2017 Renjie Wan, Boxin Shi, Ling-Yu Duan, Ah-Hwee Tan, Alex C. Kot

Removing undesired reflections from a photo taken in front of a glass is of great importance for enhancing the efficiency of visual computing systems.

Reflection Removal

A Microfacet-Based Reflectance Model for Photometric Stereo With Highly Specular Surfaces

no code implementations ICCV 2017 Lixiong Chen, Yinqiang Zheng, Boxin Shi, Art Subpa-Asa, Imari Sato

Recent developments in the field have enabled shape recovery techniques for surfaces of various types, but an effective solution to directly estimating the surface normal in the presence of highly specular reflectance remains elusive.

Radiometric Calibration for Internet Photo Collections

no code implementations CVPR 2017 Zhipeng Mo, Boxin Shi, Sai-Kit Yeung, Yasuyuki Matsushita

Radiometrically calibrating the images from Internet photo collections brings photometric analysis from lab data to big image data in the wild, but conventional calibration methods cannot be directly applied to such image data.

Polarimetric Multi-View Stereo

no code implementations CVPR 2017 Zhaopeng Cui, Jinwei Gu, Boxin Shi, Ping Tan, Jan Kautz

Multi-view stereo relies on feature correspondences for 3D reconstruction, and thus is fundamentally flawed in dealing with featureless scenes.

3D Reconstruction

Saliency Detection by Forward and Backward Cues in Deep-CNNs

1 code implementation1 Mar 2017 Nevrez Imamoglu, Chi Zhang, Wataru Shimoda, Yuming Fang, Boxin Shi

As prior knowledge of objects or object features helps us make relations for similar objects on attentional tasks, pre-trained deep convolutional neural networks (CNNs) can be used to detect salient objects on images regardless of the object class is in the network knowledge or not.

Saliency Detection

A Benchmark Dataset and Evaluation for Non-Lambertian and Uncalibrated Photometric Stereo

no code implementations CVPR 2016 Boxin Shi, Zhe Wu, Zhipeng Mo, Dinglong Duan, Sai-Kit Yeung, Ping Tan

Recent progress on photometric stereo extends the technique to deal with general materials and unknown illumination conditions.

Polarized 3D: High-Quality Depth Sensing With Polarization Cues

no code implementations ICCV 2015 Achuta Kadambi, Vage Taamazyan, Boxin Shi, Ramesh Raskar

We propose a framework to overcome these key challenges, allowing the benefits of polarization to be used to enhance depth maps.

3D Reconstruction

Photometric Stereo With Small Angular Variations

no code implementations ICCV 2015 Jian Wang, Yasuyuki Matsushita, Boxin Shi, Aswin C. Sankaranarayanan

This paper studies the effect of small angular variations in illumination directions to photometric stereo.

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