16 citations · 30 across the 12 of their papers we have counts for
12 papers
DynaVid: Learning to Generate Highly Dynamic Videos using Synthetic Motion Data
Wonjoon Jin, Jiyun Won, Janghyeok Han +4
Despite recent progress, video diffusion models still struggle to synthesize realistic videos involving highly dynamic motions or requiring fine-grained motion controllability. A c…
FloVD: Optical Flow Meets Video Diffusion Model for Enhanced Camera-Controlled Video Synthesis
Wonjoon Jin, Qi Dai, Chong Luo +2
We present FloVD, a novel video diffusion model for camera-controllable video generation. FloVD leverages optical flow to represent the motions of the camera and moving objects. Th…
Polarimetric BSSRDF Acquisition of Dynamic Faces
Hyunho Ha, Inseung Hwang, Nestor Monzon +6
Acquisition and modeling of polarized light reflection and scattering help reveal the shape, structure, and physical characteristics of an object, which is increasingly important i…
Transferable polychromatic optical encoder for neural networks
Minho Choi, Jinlin Xiang, Anna Wirth-Singh +3
Artificial neural networks (ANNs) have fundamentally transformed the field of computer vision, providing unprecedented performance. However, these ANNs for image processing demand…
Generalizable Novel-View Synthesis using a Stereo Camera
Haechan Lee, Wonjoon Jin, Seung-Hwan Baek +1
In this paper, we propose the first generalizable view synthesis approach that specifically targets multi-view stereo-camera images. Since recent stereo matching has demonstrated a…
Gyro-based Neural Single Image Deblurring
Heemin Yang, Jaesung Rim, Seungyong Lee +2
In this paper, we present GyroDeblurNet, a novel single-image deblurring method that utilizes a gyro sensor to resolve the ill-posedness of image deblurring. The gyro sensor provid…
UGPNet: Universal Generative Prior for Image Restoration
Hwayoon Lee, Kyoungkook Kang, Hyeongmin Lee +2
Recent image restoration methods can be broadly categorized into two classes: (1) regression methods that recover the rough structure of the original image without synthesizing hig…
ParamISP: Learned Forward and Inverse ISPs using Camera Parameters
Woohyeok Kim, Geonu Kim, Junyong Lee +3
RAW images are rarely shared mainly due to its excessive data size compared to their sRGB counterparts obtained by camera ISPs. Learning the forward and inverse processes of camera…
Mesh Density Adaptation for Template-based Shape Reconstruction
Yucheol Jung, Hyomin Kim, Gyeongha Hwang +2
In 3D shape reconstruction based on template mesh deformation, a regularization, such as smoothness energy, is employed to guide the reconstruction into a desirable direction. In t…
Neural Spectro-polarimetric Fields
Youngchan Kim, Wonjoon Jin, Sunghyun Cho +1
Modeling the spatial radiance distribution of light rays in a scene has been extensively explored for applications, including view synthesis. Spectrum and polarization, the wave pr…
Dr.3D: Adapting 3D GANs to Artistic Drawings
Wonjoon Jin, Nuri Ryu, Geonung Kim +2
While 3D GANs have recently demonstrated the high-quality synthesis of multi-view consistent images and 3D shapes, they are mainly restricted to photo-realistic human portraits. Th…
DynaGAN: Dynamic Few-shot Adaptation of GANs to Multiple Domains
Seongtae Kim, Kyoungkook Kang, Geonung Kim +2
Few-shot domain adaptation to multiple domains aims to learn a complex image distribution across multiple domains from a few training images. A naïve solution here is to train a se…