Search Results for author: Xiaoyu Xiang

Found 21 papers, 10 papers with code

CAD: Photorealistic 3D Generation via Adversarial Distillation

no code implementations11 Dec 2023 Ziyu Wan, Despoina Paschalidou, IAn Huang, Hongyu Liu, Bokui Shen, Xiaoyu Xiang, Jing Liao, Leonidas Guibas

The increased demand for 3D data in AR/VR, robotics and gaming applications, gave rise to powerful generative pipelines capable of synthesizing high-quality 3D objects.

Training Neural Networks on RAW and HDR Images for Restoration Tasks

no code implementations6 Dec 2023 Lei Luo, ALEXANDRE CHAPIRO, Xiaoyu Xiang, Yuchen Fan, Rakesh Ranjan, Rafal Mantiuk

Our results indicate that neural networks train significantly better on HDR and RAW images represented in display-encoded color spaces, which offer better perceptual uniformity than linear spaces.

Deblurring Denoising +2

EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything

1 code implementation1 Dec 2023 Yunyang Xiong, Bala Varadarajan, Lemeng Wu, Xiaoyu Xiang, Fanyi Xiao, Chenchen Zhu, Xiaoliang Dai, Dilin Wang, Fei Sun, Forrest Iandola, Raghuraman Krishnamoorthi, Vikas Chandra

On segment anything task such as zero-shot instance segmentation, our EfficientSAMs with SAMI-pretrained lightweight image encoders perform favorably with a significant gain (e. g., ~4 AP on COCO/LVIS) over other fast SAM models.

Image Classification Instance Segmentation +5

Efficient and Explicit Modelling of Image Hierarchies for Image Restoration

1 code implementation CVPR 2023 Yawei Li, Yuchen Fan, Xiaoyu Xiang, Denis Demandolx, Rakesh Ranjan, Radu Timofte, Luc van Gool

The aim of this paper is to propose a mechanism to efficiently and explicitly model image hierarchies in the global, regional, and local range for image restoration.

Image Deblurring Image Defocus Deblurring +1

FSID: Fully Synthetic Image Denoising via Procedural Scene Generation

1 code implementation7 Dec 2022 Gyeongmin Choe, Beibei Du, Seonghyeon Nam, Xiaoyu Xiang, Bo Zhu, Rakesh Ranjan

To address this, we have developed a procedural synthetic data generation pipeline and dataset tailored to low-level vision tasks.

Image Denoising Scene Generation +1

HIME: Efficient Headshot Image Super-Resolution with Multiple Exemplars

no code implementations28 Mar 2022 Xiaoyu Xiang, Jon Morton, Fitsum A Reda, Lucas Young, Federico Perazzi, Rakesh Ranjan, Amit Kumar, Andrea Colaco, Jan Allebach

Compared with previous methods, our network can effectively handle the misalignment between the input and the reference without requiring facial priors and learn the aggregated reference set representation in an end-to-end manner.

Image Super-Resolution

Learning Spatio-Temporal Downsampling for Effective Video Upscaling

no code implementations15 Mar 2022 Xiaoyu Xiang, Yapeng Tian, Vijay Rengarajan, Lucas Young, Bo Zhu, Rakesh Ranjan

Consequently, the inverse task of upscaling a low-resolution, low frame-rate video in space and time becomes a challenging ill-posed problem due to information loss and aliasing artifacts.


STDAN: Deformable Attention Network for Space-Time Video Super-Resolution

1 code implementation14 Mar 2022 Hai Wang, Xiaoyu Xiang, Yapeng Tian, Wenming Yang, Qingmin Liao

Second, we put forward a spatial-temporal deformable feature aggregation (STDFA) module, in which spatial and temporal contexts in dynamic video frames are adaptively captured and aggregated to enhance SR reconstruction.

Space-time Video Super-resolution Video Super-Resolution

Adversarial Open Domain Adaptation for Sketch-to-Photo Synthesis

2 code implementations12 Apr 2021 Xiaoyu Xiang, Ding Liu, Xiao Yang, Yiheng Zhu, Xiaohui Shen, Jan P. Allebach

In this paper, we explore open-domain sketch-to-photo translation, which aims to synthesize a realistic photo from a freehand sketch with its class label, even if the sketches of that class are missing in the training data.

Domain Adaptation Image-to-Image Translation +1

Feature-Align Network with Knowledge Distillation for Efficient Denoising

no code implementations2 Mar 2021 Lucas D. Young, Fitsum A. Reda, Rakesh Ranjan, Jon Morton, Jun Hu, Yazhu Ling, Xiaoyu Xiang, David Liu, Vikas Chandra

(2) A novel Feature Matching Loss that allows knowledge distillation from large denoising networks in the form of a perceptual content loss.

Efficient Neural Network Image Denoising +2

Boosting High-Level Vision with Joint Compression Artifacts Reduction and Super-Resolution

no code implementations18 Oct 2020 Xiaoyu Xiang, Qian Lin, Jan P. Allebach

In this paper, we aim to generate an artifact-free high-resolution image from a low-resolution one compressed with an arbitrary quality factor by exploring joint compression artifacts reduction (CAR) and super-resolution (SR) tasks.

Face Detection Optical Character Recognition +3

The Blessing and the Curse of the Noise behind Facial Landmark Annotations

no code implementations30 Jul 2020 Xiaoyu Xiang, Yang Cheng, Shaoyuan Xu, Qian Lin, Jan Allebach

The evolving algorithms for 2D facial landmark detection empower people to recognize faces, analyze facial expressions, etc.

Face Alignment Facial Landmark Detection

Zooming Slow-Mo: Fast and Accurate One-Stage Space-Time Video Super-Resolution

3 code implementations CVPR 2020 Xiaoyu Xiang, Yapeng Tian, Yulun Zhang, Yun Fu, Jan P. Allebach, Chenliang Xu

Rather than synthesizing missing LR video frames as VFI networks do, we firstly temporally interpolate LR frame features in missing LR video frames capturing local temporal contexts by the proposed feature temporal interpolation network.

Space-time Video Super-resolution Video Frame Interpolation +1

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