Search Results for author: Wei-Sheng Lai

Found 33 papers, 15 papers with code

Face Deblurring using Dual Camera Fusion on Mobile Phones

no code implementations23 Jul 2022 Wei-Sheng Lai, YiChang Shih, Lun-Cheng Chu, Xiaotong Wu, Sung-Fang Tsai, Michael Krainin, Deqing Sun, Chia-Kai Liang

To the best of our knowledge, our work is the first mobile solution for face motion deblurring that works reliably and robustly over thousands of images in diverse motion and lighting conditions.

Deblurring Image Deblurring

Vision Transformer for NeRF-Based View Synthesis from a Single Input Image

1 code implementation12 Jul 2022 Kai-En Lin, Lin Yen-Chen, Wei-Sheng Lai, Tsung-Yi Lin, Yi-Chang Shih, Ravi Ramamoorthi

Existing approaches condition on local image features to reconstruct a 3D object, but often render blurry predictions at viewpoints that are far away from the source view.

Novel View Synthesis

Deep Image Deblurring: A Survey

no code implementations26 Jan 2022 Kaihao Zhang, Wenqi Ren, Wenhan Luo, Wei-Sheng Lai, Bjorn Stenger, Ming-Hsuan Yang, Hongdong Li

Image deblurring is a classic problem in low-level computer vision with the aim to recover a sharp image from a blurred input image.

Deblurring Image Deblurring

Correcting Face Distortion in Wide-Angle Videos

no code implementations18 Nov 2021 Wei-Sheng Lai, YiChang Shih, Chia-Kai Liang, Ming-Hsuan Yang

Video blogs and selfies are popular social media formats, which are often captured by wide-angle cameras to show human subjects and expanded background.

Toward Real-World Super-Resolution via Adaptive Downsampling Models

no code implementations8 Sep 2021 Sanghyun Son, Jaeha Kim, Wei-Sheng Lai, Ming-Husan Yang, Kyoung Mu Lee

Most image super-resolution (SR) methods are developed on synthetic low-resolution (LR) and high-resolution (HR) image pairs that are constructed by a predetermined operation, e. g., bicubic downsampling.

Image Super-Resolution

Stylizing 3D Scene via Implicit Representation and HyperNetwork

no code implementations27 May 2021 Pei-Ze Chiang, Meng-Shiun Tsai, Hung-Yu Tseng, Wei-Sheng Lai, Wei-Chen Chiu

Our framework consists of two components: an implicit representation of the 3D scene with the neural radiance fields model, and a hypernetwork to transfer the style information into the scene representation.

Novel View Synthesis Style Transfer +1

Hybrid Neural Fusion for Full-frame Video Stabilization

2 code implementations ICCV 2021 Yu-Lun Liu, Wei-Sheng Lai, Ming-Hsuan Yang, Yung-Yu Chuang, Jia-Bin Huang

Existing video stabilization methods often generate visible distortion or require aggressive cropping of frame boundaries, resulting in smaller field of views.

Video Stabilization

Deep Online Fused Video Stabilization

1 code implementation2 Feb 2021 Zhenmei Shi, Fuhao Shi, Wei-Sheng Lai, Chia-Kai Liang, YIngyu Liang

We present a deep neural network (DNN) that uses both sensor data (gyroscope) and image content (optical flow) to stabilize videos through unsupervised learning.

Video Stabilization

Dual-Stream Fusion Network for Spatiotemporal Video Super-Resolution

1 code implementation Winter Conference on Applications of Computer Vision (WACV) 2021 Min-Yuan Tseng, Yen-Chung Chen, Yi-Lun Lee, Wei-Sheng Lai, Yi-Hsuan Tsai, Wei-Chen Chiu

Our method is based on an important observation that: even the direct cascade of prior research in spatial and temporal super-resolution can achieve the spatiotemporal upsampling, changing orders for combining them would lead to results with a complementary property.

Image Super-Resolution Video Super-Resolution

Portrait Neural Radiance Fields from a Single Image

no code implementations10 Dec 2020 Chen Gao, YiChang Shih, Wei-Sheng Lai, Chia-Kai Liang, Jia-Bin Huang

We present a method for estimating Neural Radiance Fields (NeRF) from a single headshot portrait.


Real-time Localized Photorealistic Video Style Transfer

no code implementations20 Oct 2020 Xide Xia, Tianfan Xue, Wei-Sheng Lai, Zheng Sun, Abby Chang, Brian Kulis, Jiawen Chen

We present a novel algorithm for transferring artistic styles of semantically meaningful local regions of an image onto local regions of a target video while preserving its photorealism.

Style Transfer Video Segmentation +2

Learning to See Through Obstructions with Layered Decomposition

1 code implementation11 Aug 2020 Yu-Lun Liu, Wei-Sheng Lai, Ming-Hsuan Yang, Yung-Yu Chuang, Jia-Bin Huang

We present a learning-based approach for removing unwanted obstructions, such as window reflections, fence occlusions, or adherent raindrops, from a short sequence of images captured by a moving camera.

Optical Flow Estimation

Learning to See Through Obstructions

1 code implementation CVPR 2020 Yu-Lun Liu, Wei-Sheng Lai, Ming-Hsuan Yang, Yung-Yu Chuang, Jia-Bin Huang

We present a learning-based approach for removing unwanted obstructions, such as window reflections, fence occlusions or raindrops, from a short sequence of images captured by a moving camera.

Optical Flow Estimation Reflection Removal

Gated Fusion Network for Degraded Image Super Resolution

1 code implementation2 Mar 2020 Xinyi Zhang, Hang Dong, Zhe Hu, Wei-Sheng Lai, Fei Wang, Ming-Hsuan Yang

To address this problem, we propose a dual-branch convolutional neural network to extract base features and recovered features separately.

Image Super-Resolution

Exploiting Semantics for Face Image Deblurring

no code implementations19 Jan 2020 Ziyi Shen, Wei-Sheng Lai, Tingfa Xu, Jan Kautz, Ming-Hsuan Yang

Specifically, we first use a coarse deblurring network to reduce the motion blur on the input face image.

Deblurring Face Recognition +1

Visual Question Answering on 360° Images

no code implementations10 Jan 2020 Shih-Han Chou, Wei-Lun Chao, Wei-Sheng Lai, Min Sun, Ming-Hsuan Yang

We then study two different VQA models on VQA 360, including one conventional model that takes an equirectangular image (with intrinsic distortion) as input and one dedicated model that first projects a 360 image onto cubemaps and subsequently aggregates the information from multiple spatial resolutions.

Question Answering Visual Question Answering

Video Stitching for Linear Camera Arrays

no code implementations31 Jul 2019 Wei-Sheng Lai, Orazio Gallo, Jinwei Gu, Deqing Sun, Ming-Hsuan Yang, Jan Kautz

Despite the long history of image and video stitching research, existing academic and commercial solutions still produce strong artifacts.

Autonomous Driving Spatial Interpolation

Depth-Aware Video Frame Interpolation

5 code implementations CVPR 2019 Wenbo Bao, Wei-Sheng Lai, Chao Ma, Xiaoyun Zhang, Zhiyong Gao, Ming-Hsuan Yang

The proposed model then warps the input frames, depth maps, and contextual features based on the optical flow and local interpolation kernels for synthesizing the output frame.

Optical Flow Estimation Video Frame Interpolation

Learning Blind Video Temporal Consistency

1 code implementation ECCV 2018 Wei-Sheng Lai, Jia-Bin Huang, Oliver Wang, Eli Shechtman, Ersin Yumer, Ming-Hsuan Yang

Our method takes the original unprocessed and per-frame processed videos as inputs to produce a temporally consistent video.

Colorization Image-to-Image Translation +4

Gated Fusion Network for Joint Image Deblurring and Super-Resolution

2 code implementations27 Jul 2018 Xinyi Zhang, Hang Dong, Zhe Hu, Wei-Sheng Lai, Fei Wang, Ming-Hsuan Yang

Single-image super-resolution is a fundamental task for vision applications to enhance the image quality with respect to spatial resolution.

Computational Efficiency Deblurring +2

Deep Semantic Face Deblurring

no code implementations CVPR 2018 Ziyi Shen, Wei-Sheng Lai, Tingfa Xu, Jan Kautz, Ming-Hsuan Yang

In this paper, we present an effective and efficient face deblurring algorithm by exploiting semantic cues via deep convolutional neural networks (CNNs).

Deblurring Face Recognition

Learning a Discriminative Prior for Blind Image Deblurring

no code implementations CVPR 2018 Lerenhan Li, Jinshan Pan, Wei-Sheng Lai, Changxin Gao, Nong Sang, Ming-Hsuan Yang

We present an effective blind image deblurring method based on a data-driven discriminative prior. Our work is motivated by the fact that a good image prior should favor clear images over blurred images. In this work, we formulate the image prior as a binary classifier which can be achieved by a deep convolutional neural network (CNN). The learned prior is able to distinguish whether an input image is clear or not. Embedded into the maximum a posterior (MAP) framework, it helps blind deblurring in various scenarios, including natural, face, text, and low-illumination images. However, it is difficult to optimize the deblurring method with the learned image prior as it involves a non-linear CNN. Therefore, we develop an efficient numerical approach based on the half-quadratic splitting method and gradient decent algorithm to solve the proposed model. Furthermore, the proposed model can be easily extended to non-uniform deblurring. Both qualitative and quantitative experimental results show that our method performs favorably against state-of-the-art algorithms as well as domain-specific image deblurring approaches.

Blind Image Deblurring Image Deblurring

Fast and Accurate Image Super-Resolution with Deep Laplacian Pyramid Networks

7 code implementations4 Oct 2017 Wei-Sheng Lai, Jia-Bin Huang, Narendra Ahuja, Ming-Hsuan Yang

However, existing methods often require a large number of network parameters and entail heavy computational loads at runtime for generating high-accuracy super-resolution results.

Image Reconstruction Image Super-Resolution

Semantic-driven Generation of Hyperlapse from $360^\circ$ Video

no code implementations31 Mar 2017 Wei-Sheng Lai, Yujia Huang, Neel Joshi, Chris Buehler, Ming-Hsuan Yang, Sing Bing Kang

We present a system for converting a fully panoramic ($360^\circ$) video into a normal field-of-view (NFOV) hyperlapse for an optimal viewing experience.

Video Stabilization

Learning Fully Convolutional Networks for Iterative Non-blind Deconvolution

no code implementations CVPR 2017 Jiawei Zhang, Jinshan Pan, Wei-Sheng Lai, Rynson Lau, Ming-Hsuan Yang

In this paper, we propose a fully convolutional networks for iterative non-blind deconvolution We decompose the non-blind deconvolution problem into image denoising and image deconvolution.

Image Deconvolution Image Denoising

A Comparative Study for Single Image Blind Deblurring

no code implementations CVPR 2016 Wei-Sheng Lai, Jia-Bin Huang, Zhe Hu, Narendra Ahuja, Ming-Hsuan Yang

Using these datasets, we conduct a large-scale user study to quantify the performance of several representative state-of-the-art blind deblurring algorithms.

Single-Image Blind Deblurring

Cannot find the paper you are looking for? You can Submit a new open access paper.