https://sgvr.kaist.ac.kr/publication/motion-vector-based-frame-generation-for-real-time-rendering/
Pacific Graphics Conference (PG), 2025
The demand for high frame rate rendering is rapidly increasing, especially in the graphics and gaming industries. Although recent learning-based frame interpolation methods have demonstrated promising results, they have not … Continue reading "Motion Vector-Based Frame Generation for Real-Time Rendering"
https://sgvr.kaist.ac.kr/publication/pose-free-3d-gaussian-splatting-via-shape-ray-estimation/
IEEE International Conference on Image Processing (ICIP), 2025
https://sgvr.kaist.ac.kr/publication/kinematic-fields/
TopEuropean Conference on Computer Vision (ECCV), 2024
This paper presents a novel approach for reconstructing dynamic radiance fields from monocular videos. We integrate kinematics with dynamic radiance fields, bridging the gap between the sparse nature of monocular … Continue reading "Regularizing Dynamic Radiance Fields with Kinematic Fields"
https://sgvr.kaist.ac.kr/publication/target-aware-image-denoising-for-inverse-monte-carlo-rendering/
TopACM Transactions on Graphics (SIGGRAPH 2024), 2024
Physically based differentiable rendering allows an accurate light transport simulation to be differentiated with respect to the rendering input, i.e., scene parameters, and it enables inferring scene parameters from target … Continue reading "Target-Aware Image Denoising for Inverse Monte Carlo Rendering"
https://sgvr.kaist.ac.kr/publication/semcity-semantic-scene-generation-with-triplane-diffusion/
TopIEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024
https://sgvr.kaist.ac.kr/publication/optical-neural-network-via-loose-neuron-array-and-functional-learning/
TopNature Communications, 2023
https://sgvr.kaist.ac.kr/publication/pixel-wise-guidance-for-utilizing-auxiliary-features-in-monte-carlo-denoising/
ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games (I3DG) / Proceedings of the ACM on Computer Graphics and Interactive Techniques, 2023
https://sgvr.kaist.ac.kr/publication/weakly-supervised-contrastive-learning-in-path-manifold-for-monte-carlo-image-reconstruction/
TopACM Trans. on Graphics (ToG) (proc. of SIGGRAPH), 2021
https://sgvr.kaist.ac.kr/publication/single-image-reflection-removal-with-physically-based-training-images/
TopComputer Vision and Pattern Recognition (CVPR), 2020
Oral paper
https://sgvr.kaist.ac.kr/publication/adaptive-incident-radiance-field-sampling-and-reconstruction-using-deep-reinforcement-learning/
TopACM Trans. on Graphics (ToG), 2020
https://sgvr.kaist.ac.kr/publication/feature-generation-for-adaptive-gradient-domain-path-tracing/
Pacific Graphics(PG), 2018
Received best paper honorable mention award
https://sgvr.kaist.ac.kr/publication/reflection-aware-sound-source-localization/
IEEE Int. Conf. on Robotics and Automation (ICRA), 2018
https://sgvr.kaist.ac.kr/publication/timeline-scheduling-for-out-of-core-ray-batching/
High Performance Graphics (HPG), 2017
https://sgvr.kaist.ac.kr/publication/physically-inspired-interactive-lightening-generation/
CASA 2017 and a special issue of Journal Computer Animation and Virtual Worlds(CAVW), 2017