Computer Vision: Low-level Vision[4, 6, 8, 10], 3D Vision[4, 7, 8, 10]
Robotics: Sensor Fusion[4, 7, 10], Environmental Sensing[1, 7, 9], Trajectory Prediction[2, 3]
Transdisciplinarity: Mathematics[2, 4, 7], Optics[5, 6], Social Science[1, 9]
[10] A Simple yet Universal Framework for Depth Completion
Jin-Hwi Park and Hae-Gon Jeon
The Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS), 2024
[Paper] / [Source Code]
[9] What Makes Deviant Places?
Jin-Hwi Park*, Young-Jae Park*, Ilyung Cheong, Junoh Lee, Young Eun Huh, and Hae-Gon Jeon
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) (IF: 20.8), 2024
[Paper] / [Source Code]
[8] Depth Prompting for Sensor-agnostic Depth Estimation
Jin-Hwi Park, Chanhwi Jeong, Junoh Lee and Hae-Gon Jeon
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Jun 2024
[Paper] / [Source Code]
[7] Geometry-Aware Projective Mapping for Unbounded Neural Radiance Fields
Junoh Lee, Hyunjun Jung, Jin-Hwi Park, Inhwan Bae and Hae-Gon Jeon
The Twelfth International Conference on Learning Representations (ICLR), 2024
[Paper] / [Source Code]
[6] DeepGT: Deep Learning-based Quantification of Nanosized Bioparticles in Brightfield Micrographs of Gires-Tournois Biosensor
Jiwon Kang*, Young Jin Yoo*, Jin-Hwi Park*, Joo Hwan Ko, Seungtaek Kim, Stefan G. Stanciu, Harald A. Stenmark, Jin Ah Lee, Abdullah Al Mahmud, Hae-Gon Jeon and Young Min Song
Nano Today (IF: 13.2), 2023
[Paper] / [Source Code]
[5] Full-control and Switching of Optical Fano Resonance by Continuum State Engineering
Joo Hwan Ko*, Jin-Hwi Park*, Young Jin Yoo*, Sehui Chang, Jiwon Kang, Aiguo Wu, Fang Yang, Sejeong Kim, Hae-Gon Jeon and Young Min Song
Advanced Science (IF: 14.3), 2023
[Paper] / [Source Code]
[4] Learning Affinity with Hyperbolic Representation for Spatial Propagation
Jin-Hwi Park, Jaesung Choe, Inhwan Bae and Hae-Gon Jeon
The Fortieth International Conference on Machine Learning (ICML), July 2023
[Paper] / [Source Code]
[3] Learning Pedestrian Group Representations for Multi-modal Trajectory Prediction
Inhwan Bae, Jin-Hwi Park and Hae-Gon Jeon
European Conference on Computer Vision (ECCV), Oct 2022
[Paper] / [Source Code]
[2] Non-Probability Sampling Network for Stochastic Human Trajectory Prediction
Inhwan Bae, Jin-Hwi Park and Hae-Gon Jeon
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Jun 2022
[Paper] / [Source Code]
[1] DevianceNet: Learning to Predict Deviance from A Large-scale Geo-tagged Dataset
Jin-Hwi Park*, Young-Jae Park*, Junoh Lee and Hae-Gon Jeon
The Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI), Feb 2022
[Paper] / [Source Code & Dataset]