Search Results for author: Ming-Hsuan Yang

Found 250 papers, 108 papers with code

Video Object Detection via Object-level Temporal Aggregation

no code implementations ECCV 2020 Chun-Han Yao, Chen Fang, Xiaohui Shen, Yangyue Wan, Ming-Hsuan Yang

While single-image object detectors can be naively applied to videos in a frame-by-frame fashion, the prediction is often temporally inconsistent.

Frame Video Object Detection

Autoregressive 3D Shape Generation via Canonical Mapping

no code implementations5 Apr 2022 An-Chieh Cheng, Xueting Li, Sifei Liu, Min Sun, Ming-Hsuan Yang

With the capacity of modeling long-range dependencies in sequential data, transformers have shown remarkable performances in a variety of generative tasks such as image, audio, and text generation.

3D Shape Generation Point Cloud Generation +2

Animatable Neural Radiance Fields from Monocular RGB-D

no code implementations4 Apr 2022 Tiantian Wang, Nikolaos Sarafianos, Ming-Hsuan Yang, Tony Tung

To tackle this problem, we introduce a novel method to integrate observations across frames and encode the appearance at each individual frame by utilizing the human pose that models the body shape and point clouds which cover partial part of the human as the input.


Adaptive Transformers for Robust Few-shot Cross-domain Face Anti-spoofing

no code implementations23 Mar 2022 Hsin-Ping Huang, Deqing Sun, Yaojie Liu, Wen-Sheng Chu, Taihong Xiao, Jinwei Yuan, Hartwig Adam, Ming-Hsuan Yang

While recent face anti-spoofing methods perform well under the intra-domain setups, an effective approach needs to account for much larger appearance variations of images acquired in complex scenes with different sensors for robust performance.

Face Anti-Spoofing

V2X-ViT: Vehicle-to-Everything Cooperative Perception with Vision Transformer

no code implementations20 Mar 2022 Runsheng Xu, Hao Xiang, Zhengzhong Tu, Xin Xia, Ming-Hsuan Yang, Jiaqi Ma

In this paper, we investigate the application of Vehicle-to-Everything (V2X) communication to improve the perception performance of autonomous vehicles.

3D Object Detection Autonomous Vehicles

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, which aims to recover a sharp image from a blurred input image.

Deblurring Image Deblurring

Towards a Unified Foundation Model: Jointly Pre-Training Transformers on Unpaired Images and Text

no code implementations14 Dec 2021 Qing Li, Boqing Gong, Yin Cui, Dan Kondratyuk, Xianzhi Du, Ming-Hsuan Yang, Matthew Brown

The experiments show that the resultant unified foundation transformer works surprisingly well on both the vision-only and text-only tasks, and the proposed knowledge distillation and gradient masking strategy can effectively lift the performance to approach the level of separately-trained models.

Knowledge Distillation Natural Language Understanding

An Informative Tracking Benchmark

1 code implementation13 Dec 2021 Xin Li, Qiao Liu, Wenjie Pei, Qiuhong Shen, YaoWei Wang, Huchuan Lu, Ming-Hsuan Yang

Along with the rapid progress of visual tracking, existing benchmarks become less informative due to redundancy of samples and weak discrimination between current trackers, making evaluations on all datasets extremely time-consuming.

Visual Tracking

Exploring Temporal Granularity in Self-Supervised Video Representation Learning

no code implementations8 Dec 2021 Rui Qian, Yeqing Li, Liangzhe Yuan, Boqing Gong, Ting Liu, Matthew Brown, Serge Belongie, Ming-Hsuan Yang, Hartwig Adam, Yin Cui

The training objective consists of two parts: a fine-grained temporal learning objective to maximize the similarity between corresponding temporal embeddings in the short clip and the long clip, and a persistent temporal learning objective to pull together global embeddings of the two clips.

Representation Learning Self-Supervised Learning

Learning Discriminative Shrinkage Deep Networks for Image Deconvolution

no code implementations27 Nov 2021 Pin-Hung Kuo, Jinshan Pan, Shao-Yi Chien, Ming-Hsuan Yang

Most existing methods usually formulate this problem into a maximum-a-posteriori framework and address it by designing kinds of regularization terms and data terms of the latent clear images.

Image Deconvolution Image Restoration

Learning Continuous Environment Fields via Implicit Functions

no code implementations ICLR 2022 Xueting Li, Shalini De Mello, Xiaolong Wang, Ming-Hsuan Yang, Jan Kautz, Sifei Liu

We propose a novel scene representation that encodes reaching distance -- the distance between any position in the scene to a goal along a feasible trajectory.

Trajectory Prediction

Video Frame Interpolation Transformer

1 code implementation27 Nov 2021 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.

Frame Video Frame Interpolation

Hierarchical Modular Network for Video Captioning

no code implementations24 Nov 2021 Hanhua Ye, Guorong Li, Yuankai Qi, Shuhui Wang, Qingming Huang, Ming-Hsuan Yang

(II) Predicate level, which learns the actions conditioned on highlighted objects and is supervised by the predicate in captions.

Representation Learning Video Captioning

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.

Restormer: Efficient Transformer for High-Resolution Image Restoration

5 code implementations18 Nov 2021 Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Ming-Hsuan Yang

Since convolutional neural networks (CNNs) perform well at learning generalizable image priors from large-scale data, these models have been extensively applied to image restoration and related tasks.

Color Image Denoising Deblurring +6

Semi-supervised Multi-task Learning for Semantics and Depth

no code implementations14 Oct 2021 Yufeng Wang, Yi-Hsuan Tsai, Wei-Chih Hung, Wenrui Ding, Shuo Liu, Ming-Hsuan Yang

Multi-Task Learning (MTL) aims to enhance the model generalization by sharing representations between related tasks for better performance.

Depth Estimation Multi-Task Learning +1

Burst Image Restoration and Enhancement

1 code implementation7 Oct 2021 Akshay Dudhane, Syed Waqas Zamir, Salman Khan, Fahad Shahbaz Khan, Ming-Hsuan Yang

Our central idea is to create a set of pseudo-burst features that combine complementary information from all the input burst frames to seamlessly exchange information.

Denoising Frame +3

Learning Contrastive Representation for Semantic Correspondence

no code implementations22 Sep 2021 Taihong Xiao, Sifei Liu, Shalini De Mello, Zhiding Yu, Jan Kautz, Ming-Hsuan Yang

Dense correspondence across semantically related images has been extensively studied, but still faces two challenges: 1) large variations in appearance, scale and pose exist even for objects from the same category, and 2) labeling pixel-level dense correspondences is labor intensive and infeasible to scale.

Contrastive Learning Semantic correspondence

Federated Multi-Target Domain Adaptation

no code implementations17 Aug 2021 Chun-Han Yao, Boqing Gong, Yin Cui, Hang Qi, Yukun Zhu, Ming-Hsuan Yang

We further take the server-client and inter-client domain shifts into account and pose a domain adaptation problem with one source (centralized server data) and multiple targets (distributed client data).

Domain Adaptation Federated Learning +3

Discovering 3D Parts from Image Collections

no code implementations ICCV 2021 Chun-Han Yao, Wei-Chih Hung, Varun Jampani, Ming-Hsuan Yang

Reasoning 3D shapes from 2D images is an essential yet challenging task, especially when only single-view images are at our disposal.

End-to-end Multi-modal Video Temporal Grounding

1 code implementation NeurIPS 2021 Yi-Wen Chen, Yi-Hsuan Tsai, Ming-Hsuan Yang

Specifically, we adopt RGB images for appearance, optical flow for motion, and depth maps for image structure.

Optical Flow Estimation Self-Supervised Learning

Learning 3D Dense Correspondence via Canonical Point Autoencoder

no code implementations NeurIPS 2021 An-Chieh Cheng, Xueting Li, Min Sun, Ming-Hsuan Yang, Sifei Liu

We propose a canonical point autoencoder (CPAE) that predicts dense correspondences between 3D shapes of the same category.

Self-Supervised Tracking via Target-Aware Data Synthesis

no code implementations21 Jun 2021 Xin Li, Wenjie Pei, Zikun Zhou, Zhenyu He, Huchuan Lu, Ming-Hsuan Yang

While deep-learning based tracking methods have achieved substantial progress, they entail large-scale and high-quality annotated data for sufficient training.

Representation Learning Self-Supervised Learning +1

Incremental False Negative Detection for Contrastive Learning

no code implementations ICLR 2022 Tsai-Shien Chen, Wei-Chih Hung, Hung-Yu Tseng, Shao-Yi Chien, Ming-Hsuan Yang

Self-supervised learning has recently shown great potential in vision tasks through contrastive learning, which aims to discriminate each image, or instance, in the dataset.

Contrastive Learning Self-Supervised Learning

Large-scale Unsupervised Semantic Segmentation

no code implementations6 Jun 2021 ShangHua Gao, Zhong-Yu Li, Ming-Hsuan Yang, Ming-Ming Cheng, Junwei Han, Philip Torr

Powered by the ImageNet dataset, unsupervised learning on large-scale data has made significant advances for classification tasks.

Representation Learning Unsupervised Semantic Segmentation

Learning to Stylize Novel Views

1 code implementation ICCV 2021 Hsin-Ping Huang, Hung-Yu Tseng, Saurabh Saini, Maneesh Singh, Ming-Hsuan Yang

Second, we develop point cloud aggregation modules to gather the style information of the 3D scene, and then modulate the features in the point cloud with a linear transformation matrix.

Novel View Synthesis

Intriguing Properties of Vision Transformers

1 code implementation NeurIPS 2021 Muzammal Naseer, Kanchana Ranasinghe, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Ming-Hsuan Yang

We show and analyze the following intriguing properties of ViT: (a) Transformers are highly robust to severe occlusions, perturbations and domain shifts, e. g., retain as high as 60% top-1 accuracy on ImageNet even after randomly occluding 80% of the image content.

Few-Shot Learning Semantic Segmentation

COMISR: Compression-Informed Video Super-Resolution

2 code implementations ICCV 2021 Yinxiao Li, Pengchong Jin, Feng Yang, Ce Liu, Ming-Hsuan Yang, Peyman Milanfar

Most video super-resolution methods focus on restoring high-resolution video frames from low-resolution videos without taking into account compression.

Video Super-Resolution

Decoupled Dynamic Filter Networks

1 code implementation CVPR 2021 Jingkai Zhou, Varun Jampani, Zhixiong Pi, Qiong Liu, Ming-Hsuan Yang

Inspired by recent advances in attention, DDF decouples a depth-wise dynamic filter into spatial and channel dynamic filters.

Image Classification

2.5D Visual Relationship Detection

1 code implementation26 Apr 2021 Yu-Chuan Su, Soravit Changpinyo, Xiangning Chen, Sathish Thoppay, Cho-Jui Hsieh, Lior Shapira, Radu Soricut, Hartwig Adam, Matthew Brown, Ming-Hsuan Yang, Boqing Gong

To enable progress on this task, we create a new dataset consisting of 220k human-annotated 2. 5D relationships among 512K objects from 11K images.

Depth Estimation Visual Relationship Detection

Understanding Synonymous Referring Expressions via Contrastive Features

1 code implementation20 Apr 2021 Yi-Wen Chen, Yi-Hsuan Tsai, Ming-Hsuan Yang

While prior work usually treats each sentence and attends it to an object separately, we focus on learning a referring expression comprehension model that considers the property in synonymous sentences.

Referring Expression Referring Expression Comprehension +1

Weakly Supervised Object Localization and Detection: A Survey

no code implementations16 Apr 2021 Dingwen Zhang, Junwei Han, Gong Cheng, Ming-Hsuan Yang

As an emerging and challenging problem in the computer vision community, weakly supervised object localization and detection plays an important role for developing new generation computer vision systems and has received significant attention in the past decade.

Weakly-Supervised Object Localization

The Road to Know-Where: An Object-and-Room Informed Sequential BERT for Indoor Vision-Language Navigation

1 code implementation ICCV 2021 Yuankai Qi, Zizheng Pan, Yicong Hong, Ming-Hsuan Yang, Anton Van Den Hengel, Qi Wu

Vision-and-Language Navigation (VLN) requires an agent to find a path to a remote location on the basis of natural-language instructions and a set of photo-realistic panoramas.

Vision and Language Navigation Vision-Language Navigation

In&Out : Diverse Image Outpainting via GAN Inversion

no code implementations1 Apr 2021 Yen-Chi Cheng, Chieh Hubert Lin, Hsin-Ying Lee, Jian Ren, Sergey Tulyakov, Ming-Hsuan Yang

Existing image outpainting methods pose the problem as a conditional image-to-image translation task, often generating repetitive structures and textures by replicating the content available in the input image.

Image Outpainting Image-to-Image Translation +1

ReMix: Towards Image-to-Image Translation with Limited Data

no code implementations CVPR 2021 Jie Cao, Luanxuan Hou, Ming-Hsuan Yang, Ran He, Zhenan Sun

We interpolate training samples at the feature level and propose a novel content loss based on the perceptual relations among samples.

Data Augmentation Image-to-Image Translation +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.

Frame Video Stabilization

Multi-Stage Progressive Image Restoration

5 code implementations CVPR 2021 Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Ming-Hsuan Yang, Ling Shao

At each stage, we introduce a novel per-pixel adaptive design that leverages in-situ supervised attention to reweight the local features.

Deblurring Image Deblurring +3

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

GAN Inversion: A Survey

1 code implementation14 Jan 2021 Weihao Xia, Yulun Zhang, Yujiu Yang, Jing-Hao Xue, Bolei Zhou, Ming-Hsuan Yang

GAN inversion aims to invert a given image back into the latent space of a pretrained GAN model, for the image to be faithfully reconstructed from the inverted code by the generator.

Image Manipulation Image Restoration

Low Light Image Enhancement via Global and Local Context Modeling

no code implementations4 Jan 2021 Aditya Arora, Muhammad Haris, Syed Waqas Zamir, Munawar Hayat, Fahad Shahbaz Khan, Ling Shao, Ming-Hsuan Yang

These contexts can be crucial towards inferring several image enhancement tasks, e. g., local and global contrast, brightness and color corrections; which requires cues from both local and global spatial extent.

Low-Light Image Enhancement

Benchmarking Ultra-High-Definition Image Super-Resolution

no code implementations ICCV 2021 Kaihao Zhang, Dongxu Li, Wenhan Luo, Wenqi Ren, Bjorn Stenger, Wei Liu, Hongdong Li, Ming-Hsuan Yang

Increasingly, modern mobile devices allow capturing images at Ultra-High-Definition (UHD) resolution, which includes 4K and 8K images.

Image Super-Resolution

Video Matting via Consistency-Regularized Graph Neural Networks

no code implementations ICCV 2021 Tiantian Wang, Sifei Liu, Yapeng Tian, Kai Li, Ming-Hsuan Yang

In this paper, we propose to enhance the temporal coherence by Consistency-Regularized Graph Neural Networks (CRGNN) with the aid of a synthesized video matting dataset.

Frame Image Matting +2

Online Adaptation for Consistent Mesh Reconstruction in the Wild

no code implementations NeurIPS 2020 Xueting Li, Sifei Liu, Shalini De Mello, Kihwan Kim, Xiaolong Wang, Ming-Hsuan Yang, Jan Kautz

This paper presents an algorithm to reconstruct temporally consistent 3D meshes of deformable object instances from videos in the wild.

3D Reconstruction Frame

Unsupervised Discovery of Disentangled Manifolds in GANs

1 code implementation24 Nov 2020 Yu-Ding Lu, Hsin-Ying Lee, Hung-Yu Tseng, Ming-Hsuan Yang

Interpretable generation process is beneficial to various image editing applications.

Continuous and Diverse Image-to-Image Translation via Signed Attribute Vectors

1 code implementation2 Nov 2020 Qi Mao, Hung-Yu Tseng, Hsin-Ying Lee, Jia-Bin Huang, Siwei Ma, Ming-Hsuan Yang

Generating a smooth sequence of intermediate results bridges the gap of two different domains, facilitating the morphing effect across domains.

Image-to-Image Translation Translation

Unsupervised Domain Adaptation for Spatio-Temporal Action Localization

no code implementations19 Oct 2020 Nakul Agarwal, Yi-Ting Chen, Behzad Dariush, Ming-Hsuan Yang

Spatio-temporal action localization is an important problem in computer vision that involves detecting where and when activities occur, and therefore requires modeling of both spatial and temporal features.

Object Detection Spatio-Temporal Action Localization +2

Multi-path Neural Networks for On-device Multi-domain Visual Classification

no code implementations10 Oct 2020 Qifei Wang, Junjie Ke, Joshua Greaves, Grace Chu, Gabriel Bender, Luciano Sbaiz, Alec Go, Andrew Howard, Feng Yang, Ming-Hsuan Yang, Jeff Gilbert, Peyman Milanfar

This approach effectively reduces the total number of parameters and FLOPS, encouraging positive knowledge transfer while mitigating negative interference across domains.

General Classification Neural Architecture Search +1

Every Pixel Matters: Center-aware Feature Alignment for Domain Adaptive Object Detector

1 code implementation ECCV 2020 Cheng-Chun Hsu, Yi-Hsuan Tsai, Yen-Yu Lin, Ming-Hsuan Yang

A domain adaptive object detector aims to adapt itself to unseen domains that may contain variations of object appearance, viewpoints or backgrounds.

Domain Adaptation

Learning to Caricature via Semantic Shape Transform

1 code implementation12 Aug 2020 Wenqing Chu, Wei-Chih Hung, Yi-Hsuan Tsai, Yu-Ting Chang, Yijun Li, Deng Cai, Ming-Hsuan Yang

Caricature is an artistic drawing created to abstract or exaggerate facial features of a person.


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

Spatiotemporal Contrastive Video Representation Learning

3 code implementations CVPR 2021 Rui Qian, Tianjian Meng, Boqing Gong, Ming-Hsuan Yang, Huisheng Wang, Serge Belongie, Yin Cui

Our representations are learned using a contrastive loss, where two augmented clips from the same short video are pulled together in the embedding space, while clips from different videos are pushed away.

Contrastive Learning Data Augmentation +4

Learnable Cost Volume Using the Cayley Representation

1 code implementation ECCV 2020 Taihong Xiao, Jinwei Yuan, Deqing Sun, Qifei Wang, Xin-Yu Zhang, Kehan Xu, Ming-Hsuan Yang

Cost volume is an essential component of recent deep models for optical flow estimation and is usually constructed by calculating the inner product between two feature vectors.

Optical Flow Estimation

Controllable Image Synthesis via SegVAE

no code implementations ECCV 2020 Yen-Chi Cheng, Hsin-Ying Lee, Min Sun, Ming-Hsuan Yang

We also apply an off-the-shelf image-to-image translation model to generate realistic RGB images to better understand the quality of the synthesized semantic maps.

Conditional Image Generation Image-to-Image Translation +1

RetrieveGAN: Image Synthesis via Differentiable Patch Retrieval

no code implementations ECCV 2020 Hung-Yu Tseng, Hsin-Ying Lee, Lu Jiang, Ming-Hsuan Yang, Weilong Yang

Image generation from scene description is a cornerstone technique for the controlled generation, which is beneficial to applications such as content creation and image editing.

Image Generation

Modeling Artistic Workflows for Image Generation and Editing

1 code implementation ECCV 2020 Hung-Yu Tseng, Matthew Fisher, Jingwan Lu, Yijun Li, Vladimir Kim, Ming-Hsuan Yang

People often create art by following an artistic workflow involving multiple stages that inform the overall design.

Image Generation

Semi-Supervised Learning with Meta-Gradient

1 code implementation8 Jul 2020 Xin-Yu Zhang, Taihong Xiao, HaoLin Jia, Ming-Ming Cheng, Ming-Hsuan Yang

In this work, we propose a simple yet effective meta-learning algorithm in semi-supervised learning.


WW-Nets: Dual Neural Networks for Object Detection

no code implementations15 May 2020 Mohammad K. Ebrahimpour, J. Ben Falandays, Samuel Spevack, Ming-Hsuan Yang, David C. Noelle

Inspired by this structure, we have proposed an object detection framework involving the integration of a "What Network" and a "Where Network".

Object Detection

Ventral-Dorsal Neural Networks: Object Detection via Selective Attention

no code implementations15 May 2020 Mohammad K. Ebrahimpour, Jiayun Li, Yen-Yun Yu, Jackson L. Reese, Azadeh Moghtaderi, Ming-Hsuan Yang, David C. Noelle

The coarse functional distinction between these streams is between object recognition -- the "what" of the signal -- and extracting location related information -- the "where" of the signal.

Image Classification Object Detection +1

Generalized Convolutional Forest Networks for Domain Generalization and Visual Recognition

no code implementations ICLR 2020 Jongbin Ryu, Gitaek Kwon, Ming-Hsuan Yang, Jongwoo Lim

When constructing random forests, it is of prime importance to ensure high accuracy and low correlation of individual tree classifiers for good performance.

Domain Generalization Image Classification

Multi-Scale Boosted Dehazing Network with Dense Feature Fusion

1 code implementation CVPR 2020 Hang Dong, Jinshan Pan, Lei Xiang, Zhe Hu, Xinyi Zhang, Fei Wang, Ming-Hsuan Yang

To address the issue of preserving spatial information in the U-Net architecture, we design a dense feature fusion module using the back-projection feedback scheme.

Regularizing Meta-Learning via Gradient Dropout

1 code implementation13 Apr 2020 Hung-Yu Tseng, Yi-Wen Chen, Yi-Hsuan Tsai, Sifei Liu, Yen-Yu Lin, Ming-Hsuan Yang

With the growing attention on learning-to-learn new tasks using only a few examples, meta-learning has been widely used in numerous problems such as few-shot classification, reinforcement learning, and domain generalization.

Domain Generalization Meta-Learning

Single-Image HDR Reconstruction by Learning to Reverse the Camera Pipeline

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

We model the HDRto-LDR image formation pipeline as the (1) dynamic range clipping, (2) non-linear mapping from a camera response function, and (3) quantization.

HDR Reconstruction Quantization +1

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

Deep Semantic Matching with Foreground Detection and Cycle-Consistency

no code implementations31 Mar 2020 Yun-Chun Chen, Po-Hsiang Huang, Li-Yu Yu, Jia-Bin Huang, Ming-Hsuan Yang, Yen-Yu Lin

Establishing dense semantic correspondences between object instances remains a challenging problem due to background clutter, significant scale and pose differences, and large intra-class variations.

Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition from a Domain Adaptation Perspective

1 code implementation CVPR 2020 Muhammad Abdullah Jamal, Matthew Brown, Ming-Hsuan Yang, Liqiang Wang, Boqing Gong

Object frequency in the real world often follows a power law, leading to a mismatch between datasets with long-tailed class distributions seen by a machine learning model and our expectation of the model to perform well on all classes.

Domain Adaptation Long-tail Learning +1

Collaborative Distillation for Ultra-Resolution Universal Style Transfer

1 code implementation CVPR 2020 Huan Wang, Yijun Li, Yuehai Wang, Haoji Hu, Ming-Hsuan Yang

In this work, we present a new knowledge distillation method (named Collaborative Distillation) for encoder-decoder based neural style transfer to reduce the convolutional filters.

Knowledge Distillation Style Transfer

CycleISP: Real Image Restoration via Improved Data Synthesis

6 code implementations CVPR 2020 Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Ming-Hsuan Yang, Ling Shao

This is mainly because the AWGN is not adequate for modeling the real camera noise which is signal-dependent and heavily transformed by the camera imaging pipeline.

Ranked #9 on Image Denoising on DND (using extra training data)

Image Denoising Image Restoration

Learning Enriched Features for Real Image Restoration and Enhancement

11 code implementations ECCV 2020 Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Ming-Hsuan Yang, Ling Shao

With the goal of recovering high-quality image content from its degraded version, image restoration enjoys numerous applications, such as in surveillance, computational photography, medical imaging, and remote sensing.

Image Denoising Image Enhancement +2

Self-supervised Single-view 3D Reconstruction via Semantic Consistency

no code implementations ECCV 2020 Xueting Li, Sifei Liu, Kihwan Kim, Shalini De Mello, Varun Jampani, Ming-Hsuan Yang, Jan Kautz

To the best of our knowledge, we are the first to try and solve the single-view reconstruction problem without a category-specific template mesh or semantic keypoints.

3D Reconstruction Single-View 3D Reconstruction

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.

Frame Image Super-Resolution

Weakly-Supervised Semantic Segmentation by Iterative Affinity Learning

no code implementations19 Feb 2020 Xiang Wang, Sifei Liu, Huimin Ma, Ming-Hsuan Yang

In this paper, we propose an iterative algorithm to learn such pairwise relations, which consists of two branches, a unary segmentation network which learns the label probabilities for each pixel, and a pairwise affinity network which learns affinity matrix and refines the probability map generated from the unary network.

Weakly-Supervised Semantic Segmentation

Structured Sparsification with Joint Optimization of Group Convolution and Channel Shuffle

1 code implementation19 Feb 2020 Xin-Yu Zhang, Kai Zhao, Taihong Xiao, Ming-Ming Cheng, Ming-Hsuan Yang

Recent advances in convolutional neural networks(CNNs) usually come with the expense of excessive computational overhead and memory footprint.

Network Pruning

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 +1

CrDoCo: Pixel-level Domain Transfer with Cross-Domain Consistency

no code implementations CVPR 2019 Yun-Chun Chen, Yen-Yu Lin, Ming-Hsuan Yang, Jia-Bin Huang

Unsupervised domain adaptation algorithms aim to transfer the knowledge learned from one domain to another (e. g., synthetic to real images).

Data Augmentation Image-to-Image Translation +3

RC-DARTS: Resource Constrained Differentiable Architecture Search

no code implementations30 Dec 2019 Xiaojie Jin, Jiang Wang, Joshua Slocum, Ming-Hsuan Yang, Shengyang Dai, Shuicheng Yan, Jiashi Feng

In this paper, we propose the resource constrained differentiable architecture search (RC-DARTS) method to learn architectures that are significantly smaller and faster while achieving comparable accuracy.

Image Classification One-Shot Learning

Controllable and Progressive Image Extrapolation

no code implementations25 Dec 2019 Yijun Li, Lu Jiang, Ming-Hsuan Yang

Image extrapolation aims at expanding the narrow field of view of a given image patch.

Adversarial Learning of Privacy-Preserving and Task-Oriented Representations

no code implementations22 Nov 2019 Taihong Xiao, Yi-Hsuan Tsai, Kihyuk Sohn, Manmohan Chandraker, Ming-Hsuan Yang

For instance, there could be a potential privacy risk of machine learning systems via the model inversion attack, whose goal is to reconstruct the input data from the latent representation of deep networks.

Perceptual Distance

Dancing to Music

1 code implementation NeurIPS 2019 Hsin-Ying Lee, Xiaodong Yang, Ming-Yu Liu, Ting-Chun Wang, Yu-Ding Lu, Ming-Hsuan Yang, Jan Kautz

In the analysis phase, we decompose a dance into a series of basic dance units, through which the model learns how to move.

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.


Referring Expression Object Segmentation with Caption-Aware Consistency

1 code implementation10 Oct 2019 Yi-Wen Chen, Yi-Hsuan Tsai, Tiantian Wang, Yen-Yu Lin, Ming-Hsuan Yang

To this end, we propose an end-to-end trainable comprehension network that consists of the language and visual encoders to extract feature representations from both domains.

Referring Expression Referring Expression Segmentation +1

Joint-task Self-supervised Learning for Temporal Correspondence

2 code implementations NeurIPS 2019 Xueting Li, Sifei Liu, Shalini De Mello, Xiaolong Wang, Jan Kautz, Ming-Hsuan Yang

Our learning process integrates two highly related tasks: tracking large image regions \emph{and} establishing fine-grained pixel-level associations between consecutive video frames.

Frame Object Tracking +3

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

Show, Match and Segment: Joint Weakly Supervised Learning of Semantic Matching and Object Co-segmentation

1 code implementation13 Jun 2019 Yun-Chun Chen, Yen-Yu Lin, Ming-Hsuan Yang, Jia-Bin Huang

In contrast to existing algorithms that tackle the tasks of semantic matching and object co-segmentation in isolation, our method exploits the complementary nature of the two tasks.

An Adaptive Random Path Selection Approach for Incremental Learning

1 code implementation3 Jun 2019 Jathushan Rajasegaran, Munawar Hayat, Salman Khan, Fahad Shahbaz Khan, Ling Shao, Ming-Hsuan Yang

In a conventional supervised learning setting, a machine learning model has access to examples of all object classes that are desired to be recognized during the inference stage.

Ranked #7 on Incremental Learning on ImageNet100 - 10 steps (Average Incremental Accuracy Top-5 metric)

Incremental Learning Knowledge Distillation +1

Self-supervised Audio Spatialization with Correspondence Classifier

no code implementations14 May 2019 Yu-Ding Lu, Hsin-Ying Lee, Hung-Yu Tseng, Ming-Hsuan Yang

Spatial audio is an essential medium to audiences for 3D visual and auditory experience.

Weakly-supervised Caricature Face Parsing through Domain Adaptation

1 code implementation13 May 2019 Wenqing Chu, Wei-Chih Hung, Yi-Hsuan Tsai, Deng Cai, Ming-Hsuan Yang

However, current state-of-the-art face parsing methods require large amounts of labeled data on the pixel-level and such process for caricature is tedious and labor-intensive.

Caricature Domain Adaptation +2

Few-Shot Viewpoint Estimation

no code implementations13 May 2019 Hung-Yu Tseng, Shalini De Mello, Jonathan Tremblay, Sifei Liu, Stan Birchfield, Ming-Hsuan Yang, Jan Kautz

Through extensive experimentation on the ObjectNet3D and Pascal3D+ benchmark datasets, we demonstrate that our framework, which we call MetaView, significantly outperforms fine-tuning the state-of-the-art models with few examples, and that the specific architectural innovations of our method are crucial to achieving good performance.

Meta-Learning Viewpoint Estimation

SCOPS: Self-Supervised Co-Part Segmentation

1 code implementation CVPR 2019 Wei-Chih Hung, Varun Jampani, Sifei Liu, Pavlo Molchanov, Ming-Hsuan Yang, Jan Kautz

Parts provide a good intermediate representation of objects that is robust with respect to the camera, pose and appearance variations.

DRIT++: Diverse Image-to-Image Translation via Disentangled Representations

4 code implementations2 May 2019 Hsin-Ying Lee, Hung-Yu Tseng, Qi Mao, Jia-Bin Huang, Yu-Ding Lu, Maneesh Singh, Ming-Hsuan Yang

In this work, we present an approach based on disentangled representation for generating diverse outputs without paired training images.

Image-to-Image Translation Perceptual Distance +1

Eidetic 3D LSTM: A Model for Video Prediction and Beyond

2 code implementations ICLR 2019 Yunbo Wang, Lu Jiang, Ming-Hsuan Yang, Li-Jia Li, Mingsheng Long, Li Fei-Fei

We first evaluate the E3D-LSTM network on widely-used future video prediction datasets and achieve the state-of-the-art performance.

 Ranked #1 on Video Prediction on KTH (Cond metric)

Activity Recognition Video Prediction

Target-Aware Deep Tracking

no code implementations CVPR 2019 Xin Li, Chao Ma, Baoyuan Wu, Zhenyu He, Ming-Hsuan Yang

Despite demonstrated successes for numerous vision tasks, the contributions of using pre-trained deep features for visual tracking are not as significant as that for object recognition.

Object Recognition Visual Tracking

Res2Net: A New Multi-scale Backbone Architecture

18 code implementations2 Apr 2019 Shang-Hua Gao, Ming-Ming Cheng, Kai Zhao, Xin-Yu Zhang, Ming-Hsuan Yang, Philip Torr

We evaluate the Res2Net block on all these models and demonstrate consistent performance gains over baseline models on widely-used datasets, e. g., CIFAR-100 and ImageNet.

Image Classification Instance Segmentation +2

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.

Frame Optical Flow Estimation +1

Im2Pencil: Controllable Pencil Illustration from Photographs

1 code implementation CVPR 2019 Yijun Li, Chen Fang, Aaron Hertzmann, Eli Shechtman, Ming-Hsuan Yang

We propose a high-quality photo-to-pencil translation method with fine-grained control over the drawing style.


Inserting Videos into Videos

no code implementations CVPR 2019 Donghoon Lee, Tomas Pfister, Ming-Hsuan Yang

To synthesize a realistic video, the network renders each frame based on the current input and previous frames.

Frame Object Tracking +1

Putting Humans in a Scene: Learning Affordance in 3D Indoor Environments

no code implementations CVPR 2019 Xueting Li, Sifei Liu, Kihwan Kim, Xiaolong Wang, Ming-Hsuan Yang, Jan Kautz

In order to predict valid affordances and learn possible 3D human poses in indoor scenes, we need to understand the semantic and geometric structure of a scene as well as its potential interactions with a human.

Online Multi-Object Tracking with Dual Matching Attention Networks

1 code implementation ECCV 2018 Ji Zhu, Hua Yang, Nian Liu, Minyoung Kim, Wenjun Zhang, Ming-Hsuan Yang

In this paper, we propose an online Multi-Object Tracking (MOT) approach which integrates the merits of single object tracking and data association methods in a unified framework to handle noisy detections and frequent interactions between targets.

Multi-Object Tracking online learning +1

Unseen Object Segmentation in Videos via Transferable Representations

no code implementations8 Jan 2019 Yi-Wen Chen, Yi-Hsuan Tsai, Chu-Ya Yang, Yen-Yu Lin, Ming-Hsuan Yang

The entire process is decomposed into two tasks: 1) solving a submodular function for selecting object-like segments, and 2) learning a CNN model with a transferable module for adapting seen categories in the source domain to the unseen target video.

Semantic Segmentation

PiCANet: Pixel-wise Contextual Attention Learning for Accurate Saliency Detection

2 code implementations15 Dec 2018 Nian Liu, Junwei Han, Ming-Hsuan Yang

We propose three specific formulations of the PiCANet via embedding the pixel-wise contextual attention mechanism into the pooling and convolution operations with attending to global or local contexts.

RGB Salient Object Detection Saliency Prediction +2

Context-Aware Synthesis and Placement of Object Instances

1 code implementation NeurIPS 2018 Donghoon Lee, Sifei Liu, Jinwei Gu, Ming-Yu Liu, Ming-Hsuan Yang, Jan Kautz

Learning to insert an object instance into an image in a semantically coherent manner is a challenging and interesting problem.

Scene Parsing

Deep Non-Blind Deconvolution via Generalized Low-Rank Approximation

no code implementations NeurIPS 2018 Wenqi Ren, Jiawei Zhang, Lin Ma, Jinshan Pan, Xiaochun Cao, WangMeng Zuo, Wei Liu, Ming-Hsuan Yang

In this paper, we present a deep convolutional neural network to capture the inherent properties of image degradation, which can handle different kernels and saturated pixels in a unified framework.


Joint Face Hallucination and Deblurring via Structure Generation and Detail Enhancement

no code implementations22 Nov 2018 Yibing Song, Jiawei Zhang, Lijun Gong, Shengfeng He, Linchao Bao, Jinshan Pan, Qingxiong Yang, Ming-Hsuan Yang

We first propose a facial component guided deep Convolutional Neural Network (CNN) to restore a coarse face image, which is denoted as the base image where the facial component is automatically generated from the input face image.

Deblurring Face Hallucination +1

A Fusion Approach for Multi-Frame Optical Flow Estimation

2 code implementations23 Oct 2018 Zhile Ren, Orazio Gallo, Deqing Sun, Ming-Hsuan Yang, Erik B. Sudderth, Jan Kautz

To date, top-performing optical flow estimation methods only take pairs of consecutive frames into account.

Frame Optical Flow Estimation

Deep Attentive Tracking via Reciprocative Learning

no code implementations NeurIPS 2018 Shi Pu, Yibing Song, Chao Ma, Honggang Zhang, Ming-Hsuan Yang

Visual attention, derived from cognitive neuroscience, facilitates human perception on the most pertinent subset of the sensory data.

Visual Tracking

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

Deep Regression Tracking with Shrinkage Loss

1 code implementation ECCV 2018 Xiankai Lu, Chao Ma, Bingbing Ni, Xiaokang Yang, Ian Reid, Ming-Hsuan Yang

Regression trackers directly learn a mapping from regularly dense samples of target objects to soft labels, which are usually generated by a Gaussian function, to estimate target positions.

Learning Data Terms for Non-blind Deblurring

no code implementations ECCV 2018 Jiangxin Dong, Jinshan Pan, Deqing Sun, Zhixun Su, Ming-Hsuan Yang

We propose a simple and effective discriminative framework to learn data terms that can adaptively handle blurred images in the presence of severe noise and outliers.


Learning to Blend Photos

1 code implementation ECCV 2018 Wei-Chih Hung, Jianming Zhang, Xiaohui Shen, Zhe Lin, Joon-Young Lee, Ming-Hsuan Yang

Specifically, given a foreground image and a background image, our proposed method automatically generates a set of blending photos with scores that indicate the aesthetics quality with the proposed quality network and policy network.

Sub-GAN: An Unsupervised Generative Model via Subspaces

no code implementations ECCV 2018 Jie Liang, Jufeng Yang, Hsin-Ying Lee, Kai Wang, Ming-Hsuan Yang

The recent years have witnessed significant growth in constructing robust generative models to capture informative distributions of natural data.

DFT-based Transformation Invariant Pooling Layer for Visual Classification

no code implementations ECCV 2018 Jongbin Ryu, Ming-Hsuan Yang, Jongwoo Lim

The proposed methods are extensively evaluated on various classification tasks using the ImageNet, CUB 2010-2011, MIT Indoors, Caltech 101, FMD and DTD datasets.

Classification General Classification +1

Learning Linear Transformations for Fast Arbitrary Style Transfer

1 code implementation14 Aug 2018 Xueting Li, Sifei Liu, Jan Kautz, Ming-Hsuan Yang

Recent arbitrary style transfer methods transfer second order statistics from reference image onto content image via a multiplication between content image features and a transformation matrix, which is computed from features with a pre-determined algorithm.

Domain Adaptation Style Transfer

Physics-Based Generative Adversarial Models for Image Restoration and Beyond

no code implementations2 Aug 2018 Jinshan Pan, Jiangxin Dong, Yang Liu, Jiawei Zhang, Jimmy Ren, Jinhui Tang, Yu-Wing Tai, Ming-Hsuan Yang

We present an algorithm to directly solve numerous image restoration problems (e. g., image deblurring, image dehazing, image deraining, etc.).

Deblurring Image Deblurring +3

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 Frame +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.

Deblurring Frame +2

Superpixel Sampling Networks

2 code implementations ECCV 2018 Varun Jampani, Deqing Sun, Ming-Yu Liu, Ming-Hsuan Yang, Jan Kautz

Superpixels provide an efficient low/mid-level representation of image data, which greatly reduces the number of image primitives for subsequent vision tasks.


Flow-Grounded Spatial-Temporal Video Prediction from Still Images

1 code implementation ECCV 2018 Yijun Li, Chen Fang, Jimei Yang, Zhaowen Wang, Xin Lu, Ming-Hsuan Yang

Existing video prediction methods mainly rely on observing multiple historical frames or focus on predicting the next one-frame.

Frame Video Prediction

Dynamic Scene Deblurring Using Spatially Variant Recurrent Neural Networks

1 code implementation CVPR 2018 Jiawei Zhang, Jinshan Pan, Jimmy Ren, Yibing Song, Linchao Bao, Rynson W. H. Lau, Ming-Hsuan Yang

The proposed network is composed of three deep convolutional neural networks (CNNs) and a recurrent neural network (RNN).

Ranked #6 on Deblurring on RealBlur-R (trained on GoPro) (SSIM (sRGB) metric)


Learning Superpixels With Segmentation-Aware Affinity Loss

no code implementations CVPR 2018 Wei-Chih Tu, Ming-Yu Liu, Varun Jampani, Deqing Sun, Shao-Yi Chien, Ming-Hsuan Yang, Jan Kautz

Specifically, we propose a new loss function that takes the segmentation error into account for affinity learning.


Weakly Supervised Coupled Networks for Visual Sentiment Analysis

1 code implementation CVPR 2018 Jufeng Yang, Dongyu She, Yu-Kun Lai, Paul L. Rosin, Ming-Hsuan Yang

The second branch utilizes both the holistic and localized information by coupling the sentiment map with deep features for robust classification.

General Classification Robust classification +1

Learning to Deblur Images with Exemplars

no code implementations15 May 2018 Jinshan Pan, Wenqi Ren, Zhe Hu, Ming-Hsuan Yang

However, existing methods are less effective as only few edges can be restored from blurry face images for kernel estimation.

Deblurring Image Deblurring

Correlation Tracking via Joint Discrimination and Reliability Learning

1 code implementation CVPR 2018 Chong Sun, Dong Wang, Huchuan Lu, Ming-Hsuan Yang

To address this issue, we propose a novel CF-based optimization problem to jointly model the discrimination and reliability information.

Visual Tracking

Switchable Temporal Propagation Network

1 code implementation ECCV 2018 Sifei Liu, Guangyu Zhong, Shalini De Mello, Jinwei Gu, Varun Jampani, Ming-Hsuan Yang, Jan Kautz

Our approach is based on a temporal propagation network (TPN), which models the transition-related affinity between a pair of frames in a purely data-driven manner.

Frame Video Compression

Simultaneous Fidelity and Regularization Learning for Image Restoration

1 code implementation12 Apr 2018 Dongwei Ren, WangMeng Zuo, David Zhang, Lei Zhang, Ming-Hsuan Yang

For blind deconvolution, as estimation error of blur kernel is usually introduced, the subsequent non-blind deconvolution process does not restore the latent image well.

Denoising Image Deconvolution +1

VITAL: VIsual Tracking via Adversarial Learning

no code implementations CVPR 2018 Yibing Song, Chao Ma, Xiaohe Wu, Lijun Gong, Linchao Bao, WangMeng Zuo, Chunhua Shen, Rynson Lau, Ming-Hsuan Yang

To augment positive samples, we use a generative network to randomly generate masks, which are applied to adaptively dropout input features to capture a variety of appearance changes.

Frame General Classification +1

Learning Spatial-Temporal Regularized Correlation Filters for Visual Tracking

1 code implementation CVPR 2018 Feng Li, Cheng Tian, WangMeng Zuo, Lei Zhang, Ming-Hsuan Yang

Compared with SRDCF, STRCF with hand-crafted features provides a 5 times speedup and achieves a gain of 5. 4% and 3. 6% AUC score on OTB-2015 and Temple-Color, respectively.

Visual Object Tracking Visual Tracking

Learning to Localize Sound Source in Visual Scenes

no code implementations CVPR 2018 Arda Senocak, Tae-Hyun Oh, Junsik Kim, Ming-Hsuan Yang, In So Kweon

We show that even with a few supervision, false conclusion is able to be corrected and the source of sound in a visual scene can be localized effectively.

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