Search Results for author: Seonghyeon Nam

Found 11 papers, 2 papers with code

Neural Image Representations for Multi-Image Fusion and Layer Separation

no code implementations2 Aug 2021 Seonghyeon Nam, Marcus A. Brubaker, Michael S. Brown

We propose a framework for aligning and fusing multiple images into a single view using neural image representations (NIRs), also known as implicit or coordinate-based neural representations.

Frame Optical Flow Estimation

Temporally smooth online action detection using cycle-consistent future anticipation

no code implementations16 Apr 2021 Young Hwi Kim, Seonghyeon Nam, Seon Joo Kim

Many video understanding tasks work in the offline setting by assuming that the input video is given from the start to the end.

Action Detection Autonomous Driving +2

Large Scale Multi-Illuminant (LSMI) Dataset for Developing White Balance Algorithm Under Mixed Illumination

1 code implementation ICCV 2021 Dongyoung Kim, Jinwoo Kim, Seonghyeon Nam, Dongwoo Lee, Yeonkyung Lee, Nahyup Kang, Hyong-Euk Lee, ByungIn Yoo, Jae-Joon Han, Seon Joo Kim

Images in our dataset are mostly captured with illuminants existing in the scene, and the ground truth illumination is computed by taking the difference between the images with different illumination combination.

Cross-Identity Motion Transfer for Arbitrary Objects through Pose-Attentive Video Reassembling

no code implementations ECCV 2020 Subin Jeon, Seonghyeon Nam, Seoung Wug Oh, Seon Joo Kim

To reduce the training-testing discrepancy of the self-supervised learning, a novel cross-identity training scheme is additionally introduced.

Self-Supervised Learning

Unsupervised Keypoint Learning for Guiding Class-Conditional Video Prediction

1 code implementation NeurIPS 2019 Yunji Kim, Seonghyeon Nam, In Cho, Seon Joo Kim

To generate future frames, we first detect keypoints of a moving object and predict future motion as a sequence of keypoints.

Video Prediction

Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language

no code implementations NeurIPS 2018 Seonghyeon Nam, Yunji Kim, Seon Joo Kim

Our task aims to semantically modify visual attributes of an object in an image according to the text describing the new visual appearance.

Modelling the Scene Dependent Imaging in Cameras with a Deep Neural Network

no code implementations ICCV 2017 Seonghyeon Nam, Seon Joo Kim

Often called as the radiometric calibration, the process of recovering RAW images from processed images (JPEG format in the sRGB color space) is essential for many computer vision tasks that rely on physically accurate radiance values.

Deblurring Image Deblurring

Deep Semantics-Aware Photo Adjustment

no code implementations26 Jun 2017 Seonghyeon Nam, Seon Joo Kim

Also, spatially varying photo adjustment methods have been studied by exploiting high-level features and semantic label maps.

Photo Retouching Scene Parsing

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