50 citations · 176 across the 15 of their papers we have counts for
16 papers
Progressive Text-to-3D Generation for Automatic 3D Prototyping
Han Yi, Zhedong Zheng, Xiangyu Xu +1
Text-to-3D generation is to craft a 3D object according to a natural language description. This can significantly reduce the workload for manually designing 3D models and provide a…
NU-MCC: Multiview Compressive Coding with Neighborhood Decoder and Repulsive UDF
Stefan Lionar, Xiangyu Xu, Min Lin +1
Remarkable progress has been made in 3D reconstruction from single-view RGB-D inputs. MCC is the current state-of-the-art method in this field, which achieves unprecedented success…
GLEAN: Generative Latent Bank for Image Super-Resolution and Beyond
Kelvin C. K. Chan, Xiangyu Xu, Xintao Wang +2
We show that pre-trained Generative Adversarial Networks (GANs) such as StyleGAN and BigGAN can be used as a latent bank to improve the performance of image super-resolution. While…
Cylin-Painting: Seamless {360\textdegree} Panoramic Image Outpainting and Beyond
Kang Liao, Xiangyu Xu, Chunyu Lin +3
Image outpainting gains increasing attention since it can generate the complete scene from a partial view, providing a valuable solution to construct {360\textdegree} panoramic ima…
On the Generalization of BasicVSR++ to Video Deblurring and Denoising
Kelvin C. K. Chan, Shangchen Zhou, Xiangyu Xu +1
The exploitation of long-term information has been a long-standing problem in video restoration. The recent BasicVSR and BasicVSR++ have shown remarkable performance in video super…
BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignment
Kelvin C. K. Chan, Shangchen Zhou, Xiangyu Xu +1
A recurrent structure is a popular framework choice for the task of video super-resolution. The state-of-the-art method BasicVSR adopts bidirectional propagation with feature align…
NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Methods and Results
Ren Yang, Radu Timofte, Jing Liu +69
This paper reviews the first NTIRE challenge on quality enhancement of compressed video, with a focus on the proposed methods and results. In this challenge, the new Large-scale Di…
3D Human Pose, Shape and Texture from Low-Resolution Images and Videos
Xiangyu Xu, Hao Chen, Francesc Moreno-Noguer +2
3D human pose and shape estimation from monocular images has been an active research area in computer vision. Existing deep learning methods for this task rely on high-resolution i…
Exploiting Raw Images for Real-Scene Super-Resolution
Xiangyu Xu, Yongrui Ma, Wenxiu Sun +1
Super-resolution is a fundamental problem in computer vision which aims to overcome the spatial limitation of camera sensors. While significant progress has been made in single ima…
Learning Spatial and Spatio-Temporal Pixel Aggregations for Image and Video Denoising
Xiangyu Xu, Muchen Li, Wenxiu Sun +1
Existing denoising methods typically restore clear results by aggregating pixels from the noisy input. Instead of relying on hand-crafted aggregation schemes, we propose to explici…
GLEAN: Generative Latent Bank for Large-Factor Image Super-Resolution
Kelvin C. K. Chan, Xintao Wang, Xiangyu Xu +2
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-resolut…
3D Human Shape and Pose from a Single Low-Resolution Image with Self-Supervised Learning
Xiangyu Xu, Hao Chen, Francesc Moreno-Noguer +2
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,…
AIM 2019 Challenge on Video Temporal Super-Resolution: Methods and Results
Seungjun Nah, Sanghyun Son, Radu Timofte +1
Videos contain various types and strengths of motions that may look unnaturally discontinuous in time when the recorded frame rate is low. This paper reviews the first AIM challeng…
Quadratic video interpolation
Xiangyu Xu, Li Siyao, Wenxiu Sun +2
Video interpolation is an important problem in computer vision, which helps overcome the temporal limitation of camera sensors. Existing video interpolation methods usually assume…
Towards Real Scene Super-Resolution with Raw Images
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. To solve the first prob…
Learning Deformable Kernels for Image and Video Denoising
Xiangyu Xu, Muchen Li, Wenxiu Sun
Most of the classical denoising methods restore clear results by selecting and averaging pixels in the noisy input. Instead of relying on hand-crafted selecting and averaging strat…