Search Results for author: Xiangyu Xu

Found 36 papers, 20 papers with code

GoodDrag: Towards Good Practices for Drag Editing with Diffusion Models

no code implementations10 Apr 2024 Zewei Zhang, Huan Liu, Jun Chen, Xiangyu Xu

In this paper, we introduce GoodDrag, a novel approach to improve the stability and image quality of drag editing.

Benchmarking Denoising

InfNeRF: Towards Infinite Scale NeRF Rendering with O(log n) Space Complexity

no code implementations21 Mar 2024 Jiabin Liang, Lanqing Zhang, Zhuoran Zhao, Xiangyu Xu

The conventional mesh-based Level of Detail (LoD) technique, exemplified by applications such as Google Earth and many game engines, exhibits the capability to holistically represent a large scene even the Earth, and achieves rendering with a space complexity of O(log n).

NARUTO: Neural Active Reconstruction from Uncertain Target Observations

1 code implementation29 Feb 2024 Ziyue Feng, Huangying Zhan, Zheng Chen, Qingan Yan, Xiangyu Xu, Changjiang Cai, Bing Li, Qilun Zhu, Yi Xu

We present NARUTO, a neural active reconstruction system that combines a hybrid neural representation with uncertainty learning, enabling high-fidelity surface reconstruction.

Surface Reconstruction

PlanarNeRF: Online Learning of Planar Primitives with Neural Radiance Fields

no code implementations30 Dec 2023 Zheng Chen, Qingan Yan, Huangying Zhan, Changjiang Cai, Xiangyu Xu, Yuzhong Huang, Weihan Wang, Ziyue Feng, Lantao Liu, Yi Xu

Through extensive experiments, we demonstrate the effectiveness of PlanarNeRF in various scenarios and remarkable improvement over existing works.

3D Plane Detection

Instant3D: Instant Text-to-3D Generation

no code implementations14 Nov 2023 Ming Li, Pan Zhou, Jia-Wei Liu, Jussi Keppo, Min Lin, Shuicheng Yan, Xiangyu Xu

Once trained, Instant3D is able to create a 3D object for an unseen text prompt in less than one second with a single run of a feedforward network.

3D Generation Negation +1

Towards Garment Sewing Pattern Reconstruction from a Single Image

1 code implementation7 Nov 2023 Lijuan Liu, Xiangyu Xu, Zhijie Lin, Jiabin Liang, Shuicheng Yan

In this work, we explore the challenging problem of recovering garment sewing patterns from daily photos for augmenting these applications.

Garment Reconstruction Texture Synthesis +1

Progressive Text-to-3D Generation for Automatic 3D Prototyping

1 code implementation26 Sep 2023 Han Yi, Zhedong Zheng, Xiangyu Xu, Tat-Seng Chua

We aspire for our work to pave the way for automatic 3D prototyping via natural language descriptions.

3D Generation Text to 3D

STPrivacy: Spatio-Temporal Privacy-Preserving Action Recognition

no code implementations ICCV 2023 Ming Li, Xiangyu Xu, Hehe Fan, Pan Zhou, Jun Liu, Jia-Wei Liu, Jiahe Li, Jussi Keppo, Mike Zheng Shou, Shuicheng Yan

For the first time, we introduce vision Transformers into PPAR by treating a video as a tubelet sequence, and accordingly design two complementary mechanisms, i. e., sparsification and anonymization, to remove privacy from a spatio-temporal perspective.

Action Recognition Facial Expression Recognition (FER) +2

DDM-NET: End-to-end learning of keypoint feature Detection, Description and Matching for 3D localization

1 code implementation8 Dec 2022 Xiangyu Xu, Li Guan, Enrique Dunn, Haoxiang Li, Gang Hua

In this paper, we propose an end-to-end framework that jointly learns keypoint detection, descriptor representation and cross-frame matching for the task of image-based 3D localization.

Keypoint Detection

CLIP-FLow: Contrastive Learning by semi-supervised Iterative Pseudo labeling for Optical Flow Estimation

no code implementations25 Oct 2022 Zhiqi Zhang, Nitin Bansal, Changjiang Cai, Pan Ji, Qingan Yan, Xiangyu Xu, Yi Xu

To this end, we propose CLIP-FLow, a semi-supervised iterative pseudo-labeling framework to transfer the pretraining knowledge to the target real domain.

Contrastive Learning Optical Flow Estimation +1

GLEAN: Generative Latent Bank for Image Super-Resolution and Beyond

1 code implementation29 Jul 2022 Kelvin C. K. Chan, Xiangyu Xu, Xintao Wang, Jinwei Gu, Chen Change Loy

While most existing perceptual-oriented approaches attempt to generate realistic outputs through learning with adversarial loss, our method, Generative LatEnt bANk (GLEAN), goes beyond existing practices by directly leveraging rich and diverse priors encapsulated in a pre-trained GAN.

Colorization Image Colorization +2

Cylin-Painting: Seamless {360\textdegree} Panoramic Image Outpainting and Beyond

1 code implementation18 Apr 2022 Kang Liao, Xiangyu Xu, Chunyu Lin, Wenqi Ren, Yunchao Wei, Yao Zhao

Motivated by this analysis, we present a Cylin-Painting framework that involves meaningful collaborations between inpainting and outpainting and efficiently fuses the different arrangements, with a view to leveraging their complementary benefits on a seamless cylinder.

Depth Estimation Image Outpainting +3

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

Geometry-Guided Progressive NeRF for Generalizable and Efficient Neural Human Rendering

no code implementations8 Dec 2021 Mingfei Chen, Jianfeng Zhang, Xiangyu Xu, Lijuan Liu, Yujun Cai, Jiashi Feng, Shuicheng Yan

Meanwhile, for achieving higher rendering efficiency, we introduce a progressive rendering pipeline through geometry guidance, which leverages the geometric feature volume and the predicted density values to progressively reduce the number of sampling points and speed up the rendering process.

Video Frame Interpolation Transformer

1 code implementation CVPR 2022 Zhihao Shi, Xiangyu Xu, Xiaohong Liu, Jun Chen, Ming-Hsuan Yang

Existing methods for video interpolation heavily rely on deep convolution neural networks, and thus suffer from their intrinsic limitations, such as content-agnostic kernel weights and restricted receptive field.

Video Frame Interpolation

GTT-Net: Learned Generalized Trajectory Triangulation

no code implementations ICCV 2021 Xiangyu Xu, Enrique Dunn

We present GTT-Net, a supervised learning framework for the reconstruction of sparse dynamic 3D geometry.

Event Segmentation

3D Human Texture Estimation from a Single Image with Transformers

1 code implementation ICCV 2021 Xiangyu Xu, Chen Change Loy

We propose a Transformer-based framework for 3D human texture estimation from a single image.

Garment Reconstruction

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.

Analog Video Restoration Video Enhancement +1

3D Human Pose, Shape and Texture from Low-Resolution Images and Videos

2 code implementations11 Mar 2021 Xiangyu Xu, Hao Chen, Francesc Moreno-Noguer, Laszlo A. Jeni, Fernando de la Torre

Two common approaches to deal with low-resolution images are applying super-resolution techniques to the input, which may result in unpleasant artifacts, or simply training one model for each resolution, which is impractical in many realistic applications.

3D human pose and shape estimation Contrastive Learning +1

Exploiting Raw Images for Real-Scene Super-Resolution

1 code implementation2 Feb 2021 Xiangyu Xu, Yongrui Ma, Wenxiu Sun, Ming-Hsuan Yang

In this paper, we study the problem of real-scene single image super-resolution to bridge the gap between synthetic data and real captured images.

Image Restoration Image Super-Resolution

Learning Spatial and Spatio-Temporal Pixel Aggregations for Image and Video Denoising

3 code implementations26 Jan 2021 Xiangyu Xu, Muchen Li, Wenxiu Sun, Ming-Hsuan Yang

We present a spatial pixel aggregation network and learn the pixel sampling and averaging strategies for image denoising.

Image Denoising Video Denoising

GLEAN: Generative Latent Bank for Large-Factor Image Super-Resolution

no code implementations CVPR 2021 Kelvin C. K. Chan, Xintao Wang, Xiangyu Xu, Jinwei Gu, Chen Change Loy

We show that pre-trained Generative Adversarial Networks (GANs), e. g., StyleGAN, can be used as a latent bank to improve the restoration quality of large-factor image super-resolution (SR).

Image Super-Resolution

3D Human Shape and Pose from a Single Low-Resolution Image with Self-Supervised Learning

2 code implementations ECCV 2020 Xiangyu Xu, Hao Chen, Francesc Moreno-Noguer, Laszlo A. Jeni, Fernando de la Torre

3D human shape and pose estimation from monocular images has been an active area of research in computer vision, having a substantial impact on the development of new applications, from activity recognition to creating virtual avatars.

3D Human Pose Estimation 3D Shape Reconstruction +4

Quadratic video interpolation

1 code implementation NeurIPS 2019 Xiangyu Xu, Li Si-Yao, Wenxiu Sun, Qian Yin, Ming-Hsuan Yang

Video interpolation is an important problem in computer vision, which helps overcome the temporal limitation of camera sensors.

Discrete Laplace Operator Estimation for Dynamic 3D Reconstruction

no code implementations ICCV 2019 Xiangyu Xu, Enrique Dunn

We present a general paradigm for dynamic 3D reconstruction from multiple independent and uncontrolled image sources having arbitrary temporal sampling density and distribution.

3D Reconstruction Event Segmentation

Towards Real Scene Super-Resolution with Raw Images

1 code implementation CVPR 2019 Xiangyu Xu, Yongrui Ma, Wenxiu Sun

Most existing super-resolution methods do not perform well in real scenarios due to lack of realistic training data and information loss of the model input.

Image Super-Resolution

Learning Deformable Kernels for Image and Video Denoising

2 code implementations15 Apr 2019 Xiangyu Xu, Muchen Li, Wenxiu Sun

Most of the classical denoising methods restore clear results by selecting and averaging pixels in the noisy input.

Image Denoising Video Denoising

Rendering Portraitures from Monocular Camera and Beyond

no code implementations ECCV 2018 Xiangyu Xu, Deqing Sun, Sifei Liu, Wenqi Ren, Yu-Jin Zhang, Ming-Hsuan Yang, Jian Sun

Specifically, we first exploit Convolutional Neural Networks to estimate the relative depth and portrait segmentation maps from a single input image.

Image Matting Portrait Segmentation +1

Monocular Depth Estimation with Affinity, Vertical Pooling, and Label Enhancement

no code implementations ECCV 2018 Yukang Gan, Xiangyu Xu, Wenxiu Sun, Liang Lin

While significant progress has been made in monocular depth estimation with Convolutional Neural Networks (CNNs) extracting absolute features, such as edges and textures, the depth constraint of neighboring pixels, namely relative features, has been mostly ignored by recent methods.

Monocular Depth Estimation Stereo Matching +1

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