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Junhwa Hur
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2020 – today
- 2023
- [j1]Bayram Bayramli
, Junhwa Hur, Hongtao Lu:
RAFT-MSF: Self-Supervised Monocular Scene Flow Using Recurrent Optimizer. Int. J. Comput. Vis. 131(11): 2757-2769 (2023) - [c13]Hsin-Ping Huang, Charles Herrmann, Junhwa Hur, Erika Lu, Kyle Sargent, Austin Stone, Ming-Hsuan Yang, Deqing Sun:
Self-supervised AutoFlow. CVPR 2023: 11412-11421 - [i11]Junyi Zhang, Charles Herrmann, Junhwa Hur, Luisa Polania Cabrera, Varun Jampani, Deqing Sun, Ming-Hsuan Yang:
A Tale of Two Features: Stable Diffusion Complements DINO for Zero-Shot Semantic Correspondence. CoRR abs/2305.15347 (2023) - [i10]Saurabh Saxena, Charles Herrmann, Junhwa Hur, Abhishek Kar, Mohammad Norouzi, Deqing Sun, David J. Fleet:
The Surprising Effectiveness of Diffusion Models for Optical Flow and Monocular Depth Estimation. CoRR abs/2306.01923 (2023) - 2022
- [b1]Junhwa Hur:
Joint Motion, Semantic Segmentation, Occlusion, and Depth Estimation. Technical University of Darmstadt, Germany, 2022 - [c12]Junho Lee, Junhwa Hur, Inwoo Hwang, Young Min Kim:
MasKGrasp: Mask-based Grasping for Scenes with Multiple General Real-world Objects. IROS 2022: 3137-3144 - [c11]Jung-Hee Kim, Junhwa Hur, Tien Phuoc Nguyen, Seong-Gyun Jeong:
Self-supervised surround-view depth estimation with volumetric feature fusion. NeurIPS 2022 - [i9]Bayram Bayramli, Junhwa Hur, Hongtao Lu:
RAFT-MSF: Self-Supervised Monocular Scene Flow using Recurrent Optimizer. CoRR abs/2205.01568 (2022) - [i8]Hsin-Ping Huang, Charles Herrmann, Junhwa Hur, Erika Lu, Kyle Sargent, Austin Stone, Ming-Hsuan Yang, Deqing Sun:
Self-supervised AutoFlow. CoRR abs/2212.01762 (2022) - 2021
- [c10]Junhwa Hur, Stefan Roth:
Self-Supervised Multi-Frame Monocular Scene Flow. CVPR 2021: 2684-2694 - [i7]Junhwa Hur, Stefan Roth:
Self-Supervised Multi-Frame Monocular Scene Flow. CoRR abs/2105.02216 (2021) - 2020
- [c9]Junhwa Hur, Stefan Roth:
Self-Supervised Monocular Scene Flow Estimation. CVPR 2020: 7394-7403 - [i6]Junhwa Hur, Stefan Roth:
Optical Flow Estimation in the Deep Learning Age. CoRR abs/2004.02853 (2020) - [i5]Junhwa Hur, Stefan Roth:
Self-Supervised Monocular Scene Flow Estimation. CoRR abs/2004.04143 (2020)
2010 – 2019
- 2019
- [c8]Junhwa Hur, Stefan Roth:
Iterative Residual Refinement for Joint Optical Flow and Occlusion Estimation. CVPR 2019: 5754-5763 - [i4]Junhwa Hur, Stefan Roth:
Iterative Residual Refinement for Joint Optical Flow and Occlusion Estimation. CoRR abs/1904.05290 (2019) - 2018
- [c7]Simon Meister, Junhwa Hur, Stefan Roth:
UnFlow: Unsupervised Learning of Optical Flow With a Bidirectional Census Loss. AAAI 2018: 7251-7259 - 2017
- [c6]Junhwa Hur, Stefan Roth:
MirrorFlow: Exploiting Symmetries in Joint Optical Flow and Occlusion Estimation. ICCV 2017: 312-321 - [i3]Junhwa Hur, Stefan Roth:
MirrorFlow: Exploiting Symmetries in Joint Optical Flow and Occlusion Estimation. CoRR abs/1708.05355 (2017) - [i2]Simon Meister, Junhwa Hur, Stefan Roth:
UnFlow: Unsupervised Learning of Optical Flow with a Bidirectional Census Loss. CoRR abs/1711.07837 (2017) - 2016
- [c5]Junhwa Hur, Stefan Roth:
Joint Optical Flow and Temporally Consistent Semantic Segmentation. ECCV Workshops (1) 2016: 163-177 - [i1]Junhwa Hur, Stefan Roth:
Joint Optical Flow and Temporally Consistent Semantic Segmentation. CoRR abs/1607.07716 (2016) - 2015
- [c4]Junhwa Hur, Hwasup Lim, Changsoo Park, Sang Chul Ahn:
Generalized Deformable Spatial Pyramid: Geometry-preserving dense correspondence estimation. CVPR 2015: 1392-1400 - 2014
- [c3]Junhwa Hur, Hwasup Lim, Sang Chul Ahn:
3D Deformable Spatial Pyramid for Dense 3D Motion Flow of Deformable Object. ISVC (1) 2014: 118-127 - [c2]Seung-Nam Kang, Soomok Lee, Junhwa Hur, Seung-Woo Seo:
Multi-lane detection based on accurate geometric lane estimation in highway scenarios. Intelligent Vehicles Symposium 2014: 221-226 - 2013
- [c1]Junhwa Hur, Seung-Nam Kang, Seung-Woo Seo:
Multi-lane detection in urban driving environments using conditional random fields. Intelligent Vehicles Symposium 2013: 1297-1302
Coauthor Index

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last updated on 2023-10-17 02:04 CEST by the dblp team
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