b'Kyoung Mu Lee'

research

∙ 09/16/2023

ExBluRF: Efficient Radiance Fields for Extreme Motion Blurred Images

We present ExBluRF, a novel view synthesis method for extreme motion blu...

0 Dongwoo Lee, et al. ∙

research

∙ 09/05/2023

NICE 2023 Zero-shot Image Captioning Challenge

In this report, we introduce NICE project[<https://nice.lgresearch.ai/>]...

0 Taehoon Kim, et al. ∙

research

∙ 09/05/2023

Extract-and-Adaptation Network for 3D Interacting Hand Mesh Recovery

Understanding how two hands interact with each other is a key component ...

0 JoonKyu Park, et al. ∙

research

∙ 08/18/2023

Human Part-wise 3D Motion Context Learning for Sign Language Recognition

In this paper, we propose P3D, the human part-wise motion context learni...

0 Taeryung Lee, et al. ∙

research

∙ 08/12/2023

Cyclic Test-Time Adaptation on Monocular Video for 3D Human Mesh Reconstruction

Despite recent advances in 3D human mesh reconstruction, domain gap betw...

0 Hyeongjin Nam, et al. ∙

research

∙ 07/25/2023

Overcoming Distribution Mismatch in Quantizing Image Super-Resolution Networks

Quantization is a promising approach to reduce the high computational co...

0 Cheeun Hong, et al. ∙

research

∙ 03/27/2023

Recovering 3D Hand Mesh Sequence from a Single Blurry Image: A New Dataset and Temporal Unfolding

Hands, one of the most dynamic parts of our body, suffer from blur due t...

0 Yeonguk Oh, et al. ∙

research

∙ 03/09/2023

Rethinking Self-Supervised Visual Representation Learning in Pre-training for 3D Human Pose and Shape Estimation

Recently, a few self-supervised representation learning (SSL) methods ha...

0 Hongsuk Choi, et al. ∙

research

∙ 12/16/2022

MEIL-NeRF: Memory-Efficient Incremental Learning of Neural Radiance Fields

Hinged on the representation power of neural networks, neural radiance f...

0 JaeYoung Chung, et al. ∙

research

∙ 12/12/2022

MultiAct: Long-Term 3D Human Motion Generation from Multiple Action Labels

We tackle the problem of generating long-term 3D human motion from multi...

0 Taeryung Lee, et al. ∙

research

∙ 10/02/2022

MonoNHR: Monocular Neural Human Renderer

Existing neural human rendering methods struggle with a single image inp...

0 Hongsuk Choi, et al. ∙

research

∙ 07/28/2022

Extraction of Coronary Vessels in Fluoroscopic X-Ray Sequences Using Vessel Correspondence Optimization

We present a method to extract coronary vessels from fluoroscopic x-ray ...

0 Seung Yeon Shin, et al. ∙

research

∙ 07/21/2022

CADyQ: Content-Aware Dynamic Quantization for Image Super-Resolution

Despite breakthrough advances in image super-resolution (SR) with convol...

0 Cheeun Hong, et al. ∙

research

∙ 07/20/2022

3D Clothed Human Reconstruction in the Wild

Although much progress has been made in 3D clothed human reconstruction,...

0 Gyeongsik Moon, et al. ∙

research

∙ 06/16/2022

Controllable Image Enhancement

Editing flat-looking images into stunning photographs requires skill and...

0 Heewon Kim, et al. ∙

research

∙ 04/26/2022

Attentive Fine-Grained Structured Sparsity for Image Restoration

Image restoration tasks have witnessed great performance improvement in ...

8 Junghun Oh, et al. ∙

research

∙ 03/30/2022

Pay Attention to Hidden States for Video Deblurring: Ping-Pong Recurrent Neural Networks and Selective Non-Local Attention

Video deblurring models exploit information in the neighboring frames to...

0 JoonKyu Park, et al. ∙

research

∙ 03/28/2022

HandOccNet: Occlusion-Robust 3D Hand Mesh Estimation Network

Hands are often severely occluded by objects, which makes 3D hand mesh e...

0 JoonKyu Park, et al. ∙

research

∙ 03/22/2022

AP-BSN: Self-Supervised Denoising for Real-World Images via Asymmetric PD and Blind-Spot Network

Blind-spot network (BSN) and its variants have made significant advances...

0 Wooseok Lee, et al. ∙

research

∙ 03/12/2022

Recurrence-in-Recurrence Networks for Video Deblurring

State-of-the-art video deblurring methods often adopt recurrent neural n...

0 JoonKyu Park, et al. ∙

research

∙ 02/19/2022

C2N: Practical Generative Noise Modeling for Real-World Denoising

Learning-based image denoising methods have been bounded to situations w...

0 Geonwoon Jang, et al. ∙

research

∙ 12/02/2021

Batch Normalization Tells You Which Filter is Important

The goal of filter pruning is to search for unimportant filters to remov...

0 Junghun Oh, et al. ∙

research

∙ 10/25/2021

Generative Residual Attention Network for Disease Detection

Accurate identification and localization of abnormalities from radiology...

0 Euyoung Kim, et al. ∙

research

∙ 10/15/2021

PolyNet: Polynomial Neural Network for 3D Shape Recognition with PolyShape Representation

3D shape representation and its processing have substantial effects on 3...

0 Mohsen Yavartanoo, et al. ∙

research

∙ 10/08/2021

Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning

In few-shot learning scenarios, the challenge is to generalize and perfo...

0 Sungyong Baik, et al. ∙

research

∙ 09/08/2021

Toward Real-World Super-Resolution via Adaptive Downsampling Models

Most image super-resolution (SR) methods are developed on synthetic low-...

0 Sanghyun Son, et al. ∙

research

∙ 08/19/2021

3DIAS: 3D Shape Reconstruction with Implicit Algebraic Surfaces

3D Shape representation has substantial effects on 3D shape reconstructi...

10 Mohsen Yavartanoo, et al. ∙

research

∙ 05/17/2021

Real-Time Video Super-Resolution on Smartphones with Deep Learning, Mobile AI 2021 Challenge: Report

Video super-resolution has recently become one of the most important mob...

35 Andrey Ignatov, et al. ∙

research

∙ 04/30/2021

NTIRE 2021 Challenge on Image Deblurring

Motion blur is a common photography artifact in dynamic environments tha...

0 Seungjun Nah, et al. ∙

research

∙ 04/30/2021

NTIRE 2021 Challenge on Video Super-Resolution

Super-Resolution (SR) is a fundamental computer vision task that aims to...

11 Sanghyun Son, et al. ∙

research

∙ 04/26/2021

Clean Images are Hard to Reblur: A New Clue for Deblurring

The goal of dynamic scene deblurring is to remove the motion blur presen...

12 Seungjun Nah, et al. ∙

research

∙ 04/21/2021

SRWarp: Generalized Image Super-Resolution under Arbitrary Transformation

Deep CNNs have achieved significant successes in image processing and it...

0 Sanghyun Son, et al. ∙

research

∙ 04/15/2021

3DCrowdNet: 2D Human Pose-Guided3D Crowd Human Pose and Shape Estimation in the Wild

Recovering accurate 3D human pose and shape from in-the-wild crowd scene...

0 Hongsuk Choi, et al. ∙

research

∙ 12/21/2020

DAQ: Distribution-Aware Quantization for Deep Image Super-Resolution Networks

Quantizing deep convolutional neural networks for image super-resolution...

0 Cheeun Hong, et al. ∙

research

∙ 12/21/2020

Searching for Controllable Image Restoration Networks

Diverse user preferences over images have recently led to a great amount...

2 Heewon Kim, et al. ∙

research

∙ 11/23/2020

Pose2Pose: 3D Positional Pose-Guided 3D Rotational Pose Prediction for Expressive 3D Human Pose and Mesh Estimation

Previous 3D human pose and mesh estimation methods mostly rely on only g...

8 Gyeongsik Moon, et al. ∙

research

∙ 11/23/2020

NeuralAnnot: Neural Annotator for in-the-wild Expressive 3D Human Pose and Mesh Training Sets

Recovering expressive 3D human pose and mesh from in-the-wild images is ...

0 Gyeongsik Moon, et al. ∙

research

∙ 11/17/2020

Beyond Static Features for Temporally Consistent 3D Human Pose and Shape from a Video

Despite the recent success of single image-based 3D human pose and shape...

9 Hongsuk Choi, et al. ∙

research

∙ 11/09/2020

DynaVSR: Dynamic Adaptive Blind Video Super-Resolution

Most conventional supervised super-resolution (SR) algorithms assume tha...

7 Suyoung Lee, et al. ∙

research

∙ 10/31/2020

Meta-Learning with Adaptive Hyperparameters

Despite its popularity, several recent works question the effectiveness ...

18 Sungyong Baik, et al. ∙

research

∙ 09/28/2020

AIM 2020 Challenge on Video Temporal Super-Resolution

Videos in the real-world contain various dynamics and motions that may l...

11 Sanghyun Son, et al. ∙

research

∙ 08/21/2020

Domain Adaptation of Learned Features for Visual Localization

We tackle the problem of visual localization under changing conditions, ...

0 Sungyong Baik, et al. ∙

research

∙ 08/21/2020

InterHand2.6M: A Dataset and Baseline for 3D Interacting Hand Pose Estimation from a Single RGB Image

Analysis of hand-hand interactions is a crucial step towards better unde...

0 Gyeongsik Moon, et al. ∙

research

∙ 08/20/2020

Pose2Mesh: Graph Convolutional Network for 3D Human Pose and Mesh Recovery from a 2D Human Pose

Most of the recent deep learning-based 3D human pose and mesh estimation...

0 Hongsuk Choi, et al. ∙

research

∙ 08/19/2020

DeepHandMesh: A Weakly-supervised Deep Encoder-Decoder Framework for High-fidelity Hand Mesh Modeling

Human hands play a central role in interacting with other people and obj...

11 Gyeongsik Moon, et al. ∙

research

∙ 08/09/2020

I2L-MeshNet: Image-to-Lixel Prediction Network for Accurate 3D Human Pose and Mesh Estimation from a Single RGB Image

Most of the previous image-based 3D human pose and mesh estimation metho...

0 Gyeongsik Moon, et al. ∙

research

∙ 07/14/2020

Visual Tracking by TridentAlign and Context Embedding

Recent advances in Siamese network-based visual tracking methods have en...

0 Janghoon Choi, et al. ∙

research

∙ 07/13/2020

IntegralAction: Pose-driven Feature Integration for Robust Human Action Recognition in Videos

Most current action recognition methods heavily rely on appearance infor...

0 Gyeongsik Moon, et al. ∙

research

∙ 05/04/2020

NTIRE 2020 Challenge on Image and Video Deblurring

Motion blur is one of the most common degradation artifacts in dynamic s...

7 Seungjun Nah, et al. ∙

research

∙ 05/04/2020

AIM 2019 Challenge on Video Temporal Super-Resolution: Methods and Results

Videos contain various types and strengths of motions that may look unna...

1 Seungjun Nah, et al. ∙

Kyoung Mu Lee

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