62 citations · 334 across the 27 of their papers we have counts for
28 papers
Robust Dataset Distillation by Matching Adversarial Trajectories
Wei Lai, Tianyu Ding, ren dongdong +4
Dataset distillation synthesizes compact datasets that enable models to achieve performance comparable to training on the original large-scale datasets. However, existing distillat…
Efficient Model Compression Techniques with FishLeg
Jamie McGowan, Wei Sheng Lai, Weibin Chen +7
In many domains, the most successful AI models tend to be the largest, indeed often too large to be handled by AI players with limited computational resources. To mitigate this, a…
Face Deblurring using Dual Camera Fusion on Mobile Phones
Wei-Sheng Lai, YiChang Shih, Lun-Cheng Chu +5
Motion blur of fast-moving subjects is a longstanding problem in photography and very common on mobile phones due to limited light collection efficiency, particularly in low-light…
Vision Transformer for NeRF-Based View Synthesis from a Single Input Image
Kai-En Lin, Lin Yen-Chen, Wei-Sheng Lai +3
Although neural radiance fields (NeRF) have shown impressive advances for novel view synthesis, most methods typically require multiple input images of the same scene with accurate…
Deep Image Deblurring: A Survey
Kaihao Zhang, Wenqi Ren, Wenhan Luo +4
Image deblurring is a classic problem in low-level computer vision with the aim to recover a sharp image from a blurred input image. Advances in deep learning have led to significa…
Correcting Face Distortion in Wide-Angle Videos
Wei-Sheng Lai, YiChang Shih, Chia-Kai Liang +1
Video blogs and selfies are popular social media formats, which are often captured by wide-angle cameras to show human subjects and expanded background. Unfortunately, due to persp…
Toward Real-World Super-Resolution via Adaptive Downsampling Models
Sanghyun Son, Jaeha Kim, Wei-Sheng Lai +2
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.…
Stylizing 3D Scene via Implicit Representation and HyperNetwork
Pei-Ze Chiang, Meng-Shiun Tsai, Hung-Yu Tseng +2
In this work, we aim to address the 3D scene stylization problem - generating stylized images of the scene at arbitrary novel view angles. A straightforward solution is to combine…
Deep Online Fused Video Stabilization
Zhenmei Shi, Fuhao Shi, Wei-Sheng Lai +2
We present a deep neural network (DNN) that uses both sensor data (gyroscope) and image content (optical flow) to stabilize videos through unsupervised learning. The network fuses…
Hybrid Neural Fusion for Full-frame Video Stabilization
Yu-Lun Liu, Wei-Sheng Lai, Ming-Hsuan Yang +2
Existing video stabilization methods often generate visible distortion or require aggressive cropping of frame boundaries, resulting in smaller field of views. In this work, we pre…
Portrait Neural Radiance Fields from a Single Image
Chen Gao, Yichang Shih, Wei-Sheng Lai +2
We present a method for estimating Neural Radiance Fields (NeRF) from a single headshot portrait. While NeRF has demonstrated high-quality view synthesis, it requires multiple imag…
Real-time Localized Photorealistic Video Style Transfer
Xide Xia, Tianfan Xue, Wei-sheng Lai +4
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 photore…
Learning to See Through Obstructions with Layered Decomposition
Yu-Lun Liu, Wei-Sheng Lai, Ming-Hsuan Yang +2
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 captur…
Learning to See Through Obstructions
Yu-Lun Liu, Wei-Sheng Lai, Ming-Hsuan Yang +2
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 mo…
Single-Image HDR Reconstruction by Learning to Reverse the Camera Pipeline
Yu-Lun Liu, Wei-Sheng Lai, Yu-Sheng Chen +4
Recovering a high dynamic range (HDR) image from a single low dynamic range (LDR) input image is challenging due to missing details in under-/over-exposed regions caused by quantiz…
Gated Fusion Network for Degraded Image Super Resolution
Xinyi Zhang, Hang Dong, Zhe Hu +3
Single image super resolution aims to enhance image quality with respect to spatial content, which is a fundamental task in computer vision. In this work, we address the task of si…
Exploiting Semantics for Face Image Deblurring
Ziyi Shen, Wei-Sheng Lai, Tingfa Xu +2
In this paper, we propose an effective and efficient face deblurring algorithm by exploiting semantic cues via deep convolutional neural networks. As the human faces are highly str…
Video Stitching for Linear Camera Arrays
Wei-Sheng Lai, Orazio Gallo, Jinwei Gu +3
Despite the long history of image and video stitching research, existing academic and commercial solutions still produce strong artifacts. In this work, we propose a wide-baseline…
Depth-Aware Video Frame Interpolation
Wenbo Bao, Wei-Sheng Lai, Chao Ma +3
Video frame interpolation aims to synthesize nonexistent frames in-between the original frames. While significant advances have been made from the recent deep convolutional neural…
MEMC-Net: Motion Estimation and Motion Compensation Driven Neural Network for Video Interpolation and Enhancement
Wenbo Bao, Wei-Sheng Lai, Xiaoyun Zhang +2
Motion estimation (ME) and motion compensation (MC) have been widely used for classical video frame interpolation systems over the past decades. Recently, a number of data-driven f…
Learning Blind Video Temporal Consistency
Wei-Sheng Lai, Jia-Bin Huang, Oliver Wang +3
Applying image processing algorithms independently to each frame of a video often leads to undesired inconsistent results over time. Developing temporally consistent video-based ex…
Gated Fusion Network for Joint Image Deblurring and Super-Resolution
Xinyi Zhang, Hang Dong, Zhe Hu +3
Single-image super-resolution is a fundamental task for vision applications to enhance the image quality with respect to spatial resolution. If the input image contains degraded pi…
Learning a Discriminative Prior for Blind Image Deblurring
Lerenhan Li, Jinshan Pan, Wei-Sheng Lai +3
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 image…
Deep Semantic Face Deblurring
Ziyi Shen, Wei-Sheng Lai, Tingfa Xu +2
In this paper, we present an effective and efficient face deblurring algorithm by exploiting semantic cues via deep convolutional neural networks (CNNs). As face images are highly…