65 citations · 136 across the 14 of their papers we have counts for
14 papers
EgoQR: Efficient QR Code Reading in Egocentric Settings
Mohsen Moslehpour, Yichao Lu, Pierce Chuang +7
QR codes have become ubiquitous in daily life, enabling rapid information exchange. With the increasing adoption of smart wearable devices, there is a need for efficient, and frict…
Geometry Transfer for Stylizing Radiance Fields
Hyunyoung Jung, Seonghyeon Nam, Nikolaos Sarafianos +3
Shape and geometric patterns are essential in defining stylistic identity. However, current 3D style transfer methods predominantly focus on transferring colors and textures, often…
Learning Neural Duplex Radiance Fields for Real-Time View Synthesis
Ziyu Wan, Christian Richardt, Aljaž Božič +8
Neural radiance fields (NeRFs) enable novel view synthesis with unprecedented visual quality. However, to render photorealistic images, NeRFs require hundreds of deep multilayer pe…
FSID: Fully Synthetic Image Denoising via Procedural Scene Generation
Gyeongmin Choe, Beibei Du, Seonghyeon Nam +3
For low-level computer vision and image processing ML tasks, training on large datasets is critical for generalization. However, the standard practice of relying on real-world imag…
Learning sRGB-to-Raw-RGB De-rendering with Content-Aware Metadata
Seonghyeon Nam, Abhijith Punnappurath, Marcus A. Brubaker +1
Most camera images are rendered and saved in the standard RGB (sRGB) format by the camera's hardware. Due to the in-camera photo-finishing routines, nonlinear sRGB images are undes…
Neural Image Representations for Multi-Image Fusion and Layer Separation
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 repre…
Temporally smooth online action detection using cycle-consistent future anticipation
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. However, many real-world problems require the online…
Cross-Identity Motion Transfer for Arbitrary Objects through Pose-Attentive Video Reassembling
Subin Jeon, Seonghyeon Nam, Seoung Wug Oh +1
We propose an attention-based networks for transferring motions between arbitrary objects. Given a source image(s) and a driving video, our networks animate the subject in the sour…
Learning the Loss Functions in a Discriminative Space for Video Restoration
Younghyun Jo, Jaeyeon Kang, Seoung Wug Oh +3
With more advanced deep network architectures and learning schemes such as GANs, the performance of video restoration algorithms has greatly improved recently. Meanwhile, the loss…
Unsupervised Keypoint Learning for Guiding Class-Conditional Video Prediction
Yunji Kim, Seonghyeon Nam, In Cho +1
We propose a deep video prediction model conditioned on a single image and an action class. To generate future frames, we first detect keypoints of a moving object and predict futu…
End-to-End Time-Lapse Video Synthesis from a Single Outdoor Image
Seonghyeon Nam, Chongyang Ma, Menglei Chai +3
Time-lapse videos usually contain visually appealing content but are often difficult and costly to create. In this paper, we present an end-to-end solution to synthesize a time-lap…
Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language
Seonghyeon Nam, Yunji Kim, Seon Joo Kim
This paper addresses the problem of manipulating images using natural language description. Our task aims to semantically modify visual attributes of an object in an image accordin…
Modelling the Scene Dependent Imaging in Cameras with a Deep Neural Network
Seonghyeon Nam, Seon Joo Kim
We present a novel deep learning framework that models the scene dependent image processing inside cameras. Often called as the radiometric calibration, the process of recovering R…
Deep Semantics-Aware Photo Adjustment
Seonghyeon Nam, Seon Joo Kim
Automatic photo adjustment is to mimic the photo retouching style of professional photographers and automatically adjust photos to the learned style. There have been many attempts…