Search Results for author: Shangchen Zhou

Found 19 papers, 13 papers with code

Towards Robust Blind Face Restoration with Codebook Lookup Transformer

no code implementations22 Jun 2022 Shangchen Zhou, Kelvin C. K. Chan, Chongyi Li, Chen Change Loy

In this paper, we demonstrate that a learned discrete codebook prior in a small proxy space largely reduces the uncertainty and ambiguity of restoration mapping by casting blind face restoration as a code prediction task, while providing rich visual atoms for generating high-quality faces.

Blind Face Restoration

On the Generalization of BasicVSR++ to Video Deblurring and Denoising

1 code implementation11 Apr 2022 Kelvin C. K. Chan, Shangchen Zhou, Xiangyu Xu, Chen Change Loy

The exploitation of long-term information has been a long-standing problem in video restoration.

Deblurring Denoising +2

LEDNet: Joint Low-light Enhancement and Deblurring in the Dark

no code implementations7 Feb 2022 Shangchen Zhou, Chongyi Li, Chen Change Loy

With the pipeline, we present the first large-scale dataset for joint low-light enhancement and deblurring.

Deblurring

Investigating Tradeoffs in Real-World Video Super-Resolution

1 code implementation CVPR 2022 Kelvin C. K. Chan, Shangchen Zhou, Xiangyu Xu, Chen Change Loy

The diversity and complexity of degradations in real-world video super-resolution (VSR) pose non-trivial challenges in inference and training.

Video Super-Resolution

BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignment

3 code implementations CVPR 2022 Kelvin C. K. Chan, Shangchen Zhou, Xiangyu Xu, Chen Change Loy

We show that by empowering the recurrent framework with the enhanced propagation and alignment, one can exploit spatiotemporal information across misaligned video frames more effectively.

Video Enhancement Video Restoration +1

Flexible Piecewise Curves Estimation for Photo Enhancement

no code implementations26 Oct 2020 Chongyi Li, Chunle Guo, Qiming Ai, Shangchen Zhou, Chen Change Loy

This paper presents a new method, called FlexiCurve, for photo enhancement.

Blind Face Restoration via Deep Multi-scale Component Dictionaries

1 code implementation ECCV 2020 Xiaoming Li, Chaofeng Chen, Shangchen Zhou, Xianhui Lin, WangMeng Zuo, Lei Zhang

Next, with the degraded input, we match and select the most similar component features from their corresponding dictionaries and transfer the high-quality details to the input via the proposed dictionary feature transfer (DFT) block.

Blind Face Restoration Video Super-Resolution

Cross-Scale Internal Graph Neural Network for Image Super-Resolution

1 code implementation NeurIPS 2020 Shangchen Zhou, Jiawei Zhang, WangMeng Zuo, Chen Change Loy

Specifically, we dynamically construct a cross-scale graph by searching k-nearest neighboring patches in the downsampled LR image for each query patch in the LR image.

Image Restoration Image Super-Resolution +1

Pix2Vox++: Multi-scale Context-aware 3D Object Reconstruction from Single and Multiple Images

3 code implementations22 Jun 2020 Haozhe Xie, Hongxun Yao, Shengping Zhang, Shangchen Zhou, Wenxiu Sun

A multi-scale context-aware fusion module is then introduced to adaptively select high-quality reconstructions for different parts from all coarse 3D volumes to obtain a fused 3D volume.

3D Object Reconstruction

GRNet: Gridding Residual Network for Dense Point Cloud Completion

1 code implementation ECCV 2020 Haozhe Xie, Hongxun Yao, Shangchen Zhou, Jiageng Mao, Shengping Zhang, Wenxiu Sun

In particular, we devise two novel differentiable layers, named Gridding and Gridding Reverse, to convert between point clouds and 3D grids without losing structural information.

Point Cloud Completion

Hybrid Graph Neural Networks for Crowd Counting

no code implementations31 Jan 2020 Ao Luo, Fan Yang, Xin Li, Dong Nie, Zhicheng Jiao, Shangchen Zhou, Hong Cheng

In this paper, we present a novel network structure called Hybrid Graph Neural Network (HyGnn) which targets to relieve the problem by interweaving the multi-scale features for crowd density as well as its auxiliary task (localization) together and performing joint reasoning over a graph.

Crowd Counting

SSAH: Semi-supervised Adversarial Deep Hashing with Self-paced Hard Sample Generation

no code implementations20 Nov 2019 Sheng Jin, Shangchen Zhou, Yao Liu, Chao Chen, Xiaoshuai Sun, Hongxun Yao, Xian-Sheng Hua

In this paper, we propose a novel Semi-supervised Self-pace Adversarial Hashing method, named SSAH to solve the above problems in a unified framework.

Toward 3D Object Reconstruction from Stereo Images

1 code implementation18 Oct 2019 Haozhe Xie, Hongxun Yao, Shangchen Zhou, Shengping Zhang, Xiaoshuai Sun, Wenxiu Sun

Inferring the 3D shape of an object from an RGB image has shown impressive results, however, existing methods rely primarily on recognizing the most similar 3D model from the training set to solve the problem.

3D Object Reconstruction

Spatio-Temporal Filter Adaptive Network for Video Deblurring

1 code implementation ICCV 2019 Shangchen Zhou, Jiawei Zhang, Jinshan Pan, Haozhe Xie, WangMeng Zuo, Jimmy Ren

To overcome the limitation of separate optical flow estimation, we propose a Spatio-Temporal Filter Adaptive Network (STFAN) for the alignment and deblurring in a unified framework.

Ranked #4 on Deblurring on DVD (using extra training data)

Deblurring Image Deblurring +1

DAVANet: Stereo Deblurring with View Aggregation

1 code implementation CVPR 2019 Shangchen Zhou, Jiawei Zhang, WangMeng Zuo, Haozhe Xie, Jinshan Pan, Jimmy Ren

Nowadays stereo cameras are more commonly adopted in emerging devices such as dual-lens smartphones and unmanned aerial vehicles.

Deblurring Image Deblurring

Pix2Vox: Context-aware 3D Reconstruction from Single and Multi-view Images

5 code implementations ICCV 2019 Haozhe Xie, Hongxun Yao, Xiaoshuai Sun, Shangchen Zhou, Shengping Zhang

Then, a context-aware fusion module is introduced to adaptively select high-quality reconstructions for each part (e. g., table legs) from different coarse 3D volumes to obtain a fused 3D volume.

3D Object Reconstruction 3D Reconstruction

Deep Saliency Hashing

no code implementations4 Jul 2018 Sheng Jin, Hongxun Yao, Xiaoshuai Sun, Shangchen Zhou, Lei Zhang, Xian-Sheng Hua

As the core of DSaH, the saliency loss guides the attention network to mine discriminative regions from pairs of images.

Quantization

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