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ORCIDKwang In Kim
Person information
- affiliation: Lancaster University, School of Computing & Communications
- affiliation: Max Planck Institute for Informatics
- affiliation: Saarland University, Department of Mathematics and Computer Science
- affiliation: Max Planck Institute for Intelligent Systems
- affiliation: Korea Advanced Institute of Science, Computer Science Department
- affiliation: Kyungpook National University, Department of Computer Engineering
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2020 – today
- 2024
[c50]Yunpyo An, Suyeong Park, Kwang In Kim:
Active Learning Guided by Efficient Surrogate Learners. AAAI 2024: 10874-10881- [c49]Kwang In Kim:
Robust Distributed Gradient Aggregation Using Projections onto Gradient Manifolds. AAAI 2024: 13151-13159 - [c48]Junwon Seo, Sangyoon Lee, Kwang In Kim, Jaeho Lee:
In Search of a Data Transformation that Accelerates Neural Field Training. CVPR 2024: 4830-4839 - [c47]Kwang In Kim
:
Distributed Active Client Selection With Noisy Clients Using Model Association Scores. ECCV (60) 2024: 75-92 - [c46]Jake Deane, Sinead Kearney, Kwang In Kim, Darren Cosker:
RGBT-Dog: A Parametric Model and Pose Prior For Canine Body Analysis Data Creation. WACV 2024: 6044-6054 - [i30]Sungho Jeon, Xinyue Ma, Kwang In Kim, Myeongjae Jeon:
REP: Resource-Efficient Prompting for On-device Continual Learning. CoRR abs/2406.04772 (2024) - [i29]Wonjin Lee, Kyumin Kim, Sungjae Lee, Jihun Lee, Kwang In Kim:
Piece of Table: A Divide-and-Conquer Approach for Selecting Sub-Tables in Table Question Answering. CoRR abs/2412.07629 (2024) - 2023
- [c45]Uyoung Jeong, Seungryul Baek, Hyung Jin Chang, Kwang In Kim:
BoIR: Box-Supervised Instance Representation for Multi-Person Pose Estimation. BMVC 2023: 763-764 - [i28]Yunpyo An, Suyeong Park, Kwang In Kim:
Active Deep Learning Guided by Efficient Gaussian Process Surrogates. CoRR abs/2301.02761 (2023) - [i27]Uyoung Jeong, Seungryul Baek, Hyung Jin Chang, Kwang In Kim:
BoIR: Box-Supervised Instance Representation for Multi-Person Pose Estimation. CoRR abs/2309.14072 (2023) - [i26]Junwon Seo, Sangyoon Lee, Kwang In Kim, Jaeho Lee:
In Search of a Data Transformation That Accelerates Neural Field Training. CoRR abs/2311.17094 (2023) - 2022
- [c44]Kwang In Kim:
Robust Combination of Distributed Gradients Under Adversarial Perturbations. CVPR 2022: 254-263 - [c43]Tze Ho Elden Tse, Kwang In Kim, Ales Leonardis, Hyung Jin Chang:
Collaborative Learning for Hand and Object Reconstruction with Attention-guided Graph Convolution. CVPR 2022: 1654-1664 - [c42]Kwang In Kim:
Active Label Correction Using Robust Parameter Update and Entropy Propagation. ECCV (21) 2022: 1-16 - [c41]Tze Ho Elden Tse, Zhongqun Zhang, Kwang In Kim, Ales Leonardis, Feng Zheng, Hyung Jin Chang:
S2Contact: Graph-Based Network for 3D Hand-Object Contact Estimation with Semi-supervised Learning. ECCV (1) 2022: 568-584 - [i25]Tze Ho Elden Tse, Kwang In Kim, Ales Leonardis, Hyung Jin Chang:
Collaborative Learning for Hand and Object Reconstruction with Attention-guided Graph Convolution. CoRR abs/2204.13062 (2022) - [i24]Tze Ho Elden Tse, Zhongqun Zhang, Kwang In Kim, Ales Leonardis, Feng Zheng, Hyung Jin Chang:
S2Contact: Graph-based Network for 3D Hand-Object Contact Estimation with Semi-Supervised Learning. CoRR abs/2208.00874 (2022) - 2021
- [c40]Youssef Alami Mejjati, Isa Milefchik, Aaron Gokaslan, Oliver Wang, Kwang In Kim, James Tompkin:
GaussiGAN: Controllable Image Synthesis with 3D Gaussians from Unposed Silhouettes. BMVC 2021: 371 - [c39]Kwanyoung Kim, Dongwon Park, Kwang In Kim, Se Young Chun:
Task-Aware Variational Adversarial Active Learning. CVPR 2021: 8166-8175 - [c38]Kwang In Kim, James Tompkin:
Testing using Privileged Information by Adapting Features with Statistical Dependence. ICCV 2021: 9385-9393 - [c37]Donguk Kim, Kwang In Kim, Seungryul Baek:
End-to-End Detection and Pose Estimation of Two Interacting Hands. ICCV 2021: 11169-11178 - [c36]Kwang In Kim:
Improving Predictors via Combination Across Diverse Task Categories. ICML 2021: 5475-5485 - [i23]Youssef A. Mejjati, Isa Milefchik, Aaron Gokaslan, Oliver Wang, Kwang In Kim, James Tompkin:
GaussiGAN: Controllable Image Synthesis with 3D Gaussians from Unposed Silhouettes. CoRR abs/2106.13215 (2021) - [i22]Jake Deane, Sinead Kearney, Kwang In Kim, Darren Cosker:
DynaDog+T: A Parametric Animal Model for Synthetic Canine Image Generation. CoRR abs/2107.07330 (2021) - [i21]Kwang In Kim, James Tompkin:
Testing using Privileged Information by Adapting Features with Statistical Dependence. CoRR abs/2111.02865 (2021) - 2020
- [c35]Seungryul Baek, Kwang In Kim, Tae-Kyun Kim:
Weakly-Supervised Domain Adaptation via GAN and Mesh Model for Estimating 3D Hand Poses Interacting Objects. CVPR 2020: 6120-6130 - [c34]Sinead Kearney, Wenbin Li, Martin Parsons, Kwang In Kim, Darren Cosker:
RGBD-Dog: Predicting Canine Pose from RGBD Sensors. CVPR 2020: 8333-8342 - [c33]Youssef A. Mejjati, Celso F. Gomez, Kwang In Kim, Eli Shechtman, Zoya Bylinskii:
Look Here! A Parametric Learning Based Approach to Redirect Visual Attention. ECCV (23) 2020: 343-361 - [c32]Kwang In Kim, Christian Richardt, Hyung Jin Chang:
Combining Task Predictors via Enhancing Joint Predictability. ECCV (16) 2020: 439-455 - [i20]Youssef Alami Mejjati, Zejiang Shen, Michael Snower, Aaron Gokaslan, Oliver Wang, James Tompkin, Kwang In Kim:
Generating Object Stamps. CoRR abs/2001.02595 (2020) - [i19]Kwan-Young Kim, Dongwon Park, Kwang In Kim, Se Young Chun:
Task-Aware Variational Adversarial Active Learning. CoRR abs/2002.04709 (2020) - [i18]Sinead Kearney, Wenbin Li, Martin Parsons, Kwang In Kim, Darren Cosker:
RGBD-Dog: Predicting Canine Pose from RGBD Sensors. CoRR abs/2004.07788 (2020) - [i17]Kwang In Kim, Christian Richardt, Hyung Jin Chang:
Combining Task Predictors via Enhancing Joint Predictability. CoRR abs/2007.08012 (2020) - [i16]Youssef Alami Mejjati, Celso F. Gomez, Kwang In Kim, Eli Shechtman, Zoya Bylinskii:
Look here! A parametric learning based approach to redirect visual attention. CoRR abs/2008.05413 (2020)
2010 – 2019
- 2019
- [c31]Dushyant Mehta, Kwang In Kim, Christian Theobalt:
On Implicit Filter Level Sparsity in Convolutional Neural Networks. CVPR 2019: 520-528 - [c30]Seungryul Baek, Kwang In Kim, Tae-Kyun Kim:
Pushing the Envelope for RGB-Based Dense 3D Hand Pose Estimation via Neural Rendering. CVPR 2019: 1067-1076 - [c29]Kwang In Kim, Hyung Jin Chang:
Joint Manifold Diffusion for Combining Predictions on Decoupled Observations. CVPR 2019: 7549-7557 - [i15]Seungryul Baek, Kwang In Kim, Tae-Kyun Kim:
Pushing the Envelope for RGB-based Dense 3D Hand Pose Estimation via Neural Rendering. CoRR abs/1904.04196 (2019) - [i14]Kwang In Kim, Hyung Jin Chang:
Joint Manifold Diffusion for Combining Predictions on Decoupled Observations. CoRR abs/1904.05159 (2019) - [i13]Dushyant Mehta, Kwang In Kim, Christian Theobalt:
Implicit Filter Sparsification In Convolutional Neural Networks. CoRR abs/1905.04967 (2019) - 2018
- [c28]Juil Sock, Kwang In Kim, Caner Sahin, Tae-Kyun Kim:
Multi-Task Deep Networks for Depth-Based 6D Object Pose and Joint Registration in Crowd Scenarios. BMVC 2018: 90 - [c27]Yassir Saquil, Kwang In Kim, Peter M. Hall:
Ranking CGANs: Subjective Control over Semantic Image Attributes. BMVC 2018: 131 - [c26]Youssef A. Mejjati, Darren Cosker, Kwang In Kim:
Multi-Task Learning by Maximizing Statistical Dependence. CVPR 2018: 3465-3473 - [c25]Kwang In Kim, Juhyun Park, James Tompkin:
High-Order Tensor Regularization With Application to Attribute Ranking. CVPR 2018: 4349-4357 - [c24]Seungryul Baek, Kwang In Kim, Tae-Kyun Kim:
Augmented Skeleton Space Transfer for Depth-Based Hand Pose Estimation. CVPR 2018: 8330-8339 - [c23]Aaron Gokaslan, Vivek Ramanujan, Daniel Ritchie, Kwang In Kim, James Tompkin:
Improving Shape Deformation in Unsupervised Image-to-Image Translation. ECCV (12) 2018: 662-678 - [c22]Youssef Alami Mejjati, Christian Richardt, James Tompkin, Darren Cosker, Kwang In Kim:
Unsupervised Attention-guided Image-to-Image Translation. NeurIPS 2018: 3697-3707 - [i12]Yassir Saquil, Kwang In Kim, Peter M. Hall:
Ranking Generative Adversarial Networks: Subjective Control over Semantic Image Attributes. CoRR abs/1804.04082 (2018) - [i11]Seungryul Baek, Kwang In Kim, Tae-Kyun Kim:
Augmented Skeleton Space Transfer for Depth-based Hand Pose Estimation. CoRR abs/1805.04497 (2018) - [i10]Youssef A. Mejjati, Christian Richardt, James Tompkin, Darren Cosker, Kwang In Kim:
Unsupervised Attention-guided Image to Image Translation. CoRR abs/1806.02311 (2018) - [i9]Juil Sock, Kwang In Kim, Caner Sahin, Tae-Kyun Kim:
Multi-Task Deep Networks for Depth-Based 6D Object Pose and Joint Registration in Crowd Scenarios. CoRR abs/1806.03891 (2018) - [i8]Aaron Gokaslan, Vivek Ramanujan, Daniel Ritchie, Kwang In Kim, James Tompkin:
Improving Shape Deformation in Unsupervised Image-to-Image Translation. CoRR abs/1808.04325 (2018) - [i7]Dushyant Mehta, Kwang In Kim, Christian Theobalt:
On Implicit Filter Level Sparsity in Convolutional Neural Networks. CoRR abs/1811.12495 (2018) - 2017
- [c21]James Tompkin, Kwang In Kim, Hanspeter Pfister, Christian Theobalt:
Criteria Sliders: Learning Continuous Database Criteria via Interactive Ranking. BMVC 2017 - [c20]Kwang In Kim, James Tompkin, Christian Richardt:
Predictor Combination at Test Time. ICCV 2017: 3573-3581 - [c19]Guixin Ye, Zhanyong Tang, Dingyi Fang, Xiaojiang Chen, Kwang In Kim, Ben Taylor, Zheng Wang:
Cracking Android Pattern Lock in Five Attempts. NDSS 2017 - [c18]Seungryul Baek, Kwang In Kim, Tae-Kyun Kim:
Real-Time Online Action Detection Forests Using Spatio-Temporal Contexts. WACV 2017: 158-167 - [i6]Seungryul Baek, Kwang In Kim, Tae-Kyun Kim:
Deep Convolutional Decision Jungle for Image Classification. CoRR abs/1706.02003 (2017) - [i5]James Tompkin, Kwang In Kim, Hanspeter Pfister, Christian Theobalt:
Criteria Sliders: Learning Continuous Database Criteria via Interactive Ranking. CoRR abs/1706.03863 (2017) - 2016
- [c17]Kwang In Kim:
Semi-supervised Learning Based on Joint Diffusion of Graph Functions and Laplacians. ECCV (5) 2016: 713-729 - [i4]Kwang In Kim, James Tompkin, Hanspeter Pfister, Christian Theobalt:
Local High-order Regularization on Data Manifolds. CoRR abs/1602.03805 (2016) - [i3]Kwang In Kim, James Tompkin, Hanspeter Pfister, Christian Theobalt:
Semi-supervised Learning with Explicit Relationship Regularization. CoRR abs/1602.03808 (2016) - [i2]Kwang In Kim, James Tompkin, Hanspeter Pfister, Christian Theobalt:
Context-guided diffusion for label propagation on graphs. CoRR abs/1602.06439 (2016) - [i1]Seungryul Baek, Kwang In Kim, Tae-Kyun Kim:
Real-time Online Action Detection Forests using Spatio-temporal Contexts. CoRR abs/1610.09334 (2016) - 2015
- [j18]Ahmed Elhayek, Carsten Stoll, Kwang In Kim, Christian Theobalt:
Outdoor Human Motion Capture by Simultaneous Optimization of Pose and Camera Parameters. Comput. Graph. Forum 34(6): 86-98 (2015) - [j17]Younghee Kwon, Kwang In Kim, James Tompkin, Jin Hyung Kim, Christian Theobalt:
Efficient Learning of Image Super-Resolution and Compression Artifact Removal with Semi-Local Gaussian Processes. IEEE Trans. Pattern Anal. Mach. Intell. 37(9): 1792-1805 (2015) - [j16]Helge Rhodin, James Tompkin, Kwang In Kim, Edilson de Aguiar, Hanspeter Pfister, Hans-Peter Seidel, Christian Theobalt:
Generalizing wave gestures from sparse examples for real-time character control. ACM Trans. Graph. 34(6): 181:1-181:12 (2015) - [c16]Kwang In Kim, James Tompkin, Hanspeter Pfister, Christian Theobalt:
Semi-supervised learning with explicit relationship regularization. CVPR 2015: 2188-2196 - [c15]Kwang In Kim, James Tompkin, Hanspeter Pfister, Christian Theobalt:
Local high-order regularization on data manifolds. CVPR 2015: 5473-5481 - [c14]Kwang In Kim, James Tompkin, Hanspeter Pfister, Christian Theobalt:
Context-Guided Diffusion for Label Propagation on Graphs. ICCV 2015: 2776-2784 - 2014
- [j15]Helge Rhodin, James Tompkin, Kwang In Kim, Kiran Varanasi, Hans-Peter Seidel, Christian Theobalt:
Interactive motion mapping for real-time character control. Comput. Graph. Forum 33(2): 273-282 (2014) - 2013
- [j14]James Tompkin, Min H. Kim, Kwang In Kim, Jan Kautz, Christian Theobalt:
Preference and artifact analysis for video transitions of places. ACM Trans. Appl. Percept. 10(3): 13:1-13:19 (2013) - [j13]Miguel Granados, Kwang In Kim, James Tompkin, Christian Theobalt:
Automatic noise modeling for ghost-free HDR reconstruction. ACM Trans. Graph. 32(6): 201:1-201:10 (2013) - [c13]Frank Lenzen, Kwang In Kim, Henrik Schäfer, Rahul Nair, Stephan Meister, Florian Becker, Christoph S. Garbe, Christian Theobalt:
Denoising Strategies for Time-of-Flight Data. Time-of-Flight and Depth Imaging 2013: 25-45 - [c12]Kwang In Kim, James Tompkin, Christian Theobalt:
Curvature-Aware Regularization on Riemannian Submanifolds. ICCV 2013: 881-888 - 2012
- [j12]Miguel Granados, James Tompkin, Kwang In Kim, Oliver Grau, Jan Kautz, Christian Theobalt:
How Not to Be Seen - Object Removal from Videos of Crowded Scenes. Comput. Graph. Forum 31(2pt1): 219-228 (2012) - [j11]Robert Herzog, Martin Cadík, Tunç Ozan Aydin, Kwang In Kim, Karol Myszkowski, Hans-Peter Seidel:
NoRM: No-Reference Image Quality Metric for Realistic Image Synthesis. Comput. Graph. Forum 31(2pt3): 545-554 (2012) - [j10]James Tompkin, Kwang In Kim, Jan Kautz, Christian Theobalt:
Videoscapes: exploring sparse, unstructured video collections. ACM Trans. Graph. 31(4): 68:1-68:12 (2012) - [c11]Younghee Kwon, Kwang In Kim, Jin Kim, Christian Theobalt:
Efficient Learning-based Image Enhancement: Application to Super-resolution and Compression Artifact Removal. BMVC 2012: 1-12 - [c10]Ahmed Elhayek, Carsten Stoll, Nils Hasler, Kwang In Kim, Hans-Peter Seidel, Christian Theobalt:
Spatio-temporal motion tracking with unsynchronized cameras. CVPR 2012: 1870-1877 - [c9]Ahmed Elhayek, Carsten Stoll, Kwang In Kim, Hans-Peter Seidel, Christian Theobalt:
Feature-Based Multi-video Synchronization with Subframe Accuracy. DAGM/OAGM Symposium 2012: 266-275 - [c8]Kwang In Kim, James Tompkin, Martin Theobald, Jan Kautz, Christian Theobalt:
Match Graph Construction for Large Image Databases. ECCV (1) 2012: 272-285 - [c7]Miguel Granados, Kwang In Kim, James Tompkin, Jan Kautz, Christian Theobalt:
Background Inpainting for Videos with Dynamic Objects and a Free-Moving Camera. ECCV (1) 2012: 682-695 - 2010
- [j9]Kwang In Kim, Younghee Kwon:
Single-Image Super-Resolution Using Sparse Regression and Natural Image Prior. IEEE Trans. Pattern Anal. Mach. Intell. 32(6): 1127-1133 (2010)
2000 – 2009
- 2009
- [c6]Kwang In Kim, Florian Steinke, Matthias Hein:
Semi-supervised Regression using Hessian energy with an application to semi-supervised dimensionality reduction. NIPS 2009: 979-987 - 2008
- [c5]Kwang In Kim, Younghee Kwon:
Example-Based Learning for Single-Image Super-Resolution. DAGM-Symposium 2008: 456-465 - [c4]Pia Breuer, Kwang In Kim, Wolf Kienzle, Bernhard Schölkopf, Volker Blanz:
Automatic 3D face reconstruction from single images or video. FG 2008: 1-8 - [c3]Christian Walder, Kwang In Kim, Bernhard Schölkopf:
Sparse multiscale gaussian process regression. ICML 2008: 1112-1119 - 2005
- [j8]Kwang In Kim, Matthias O. Franz, Bernhard Schölkopf:
Iterative Kernel Principal Component Analysis for Image Modeling. IEEE Trans. Pattern Anal. Mach. Intell. 27(9): 1351-1366 (2005) - 2004
- [j7]Keechul Jung, Kwang In Kim, Anil K. Jain:
Text information extraction in images and video: a survey. Pattern Recognit. 37(5): 977-997 (2004) - 2003
- [j6]Kwang In Kim, Keechul Jung, Jin Hyung Kim:
Texture-Based Approach for Text Detection in Images Using Support Vector Machines and Continuously Adaptive Mean Shift Algorithm. IEEE Trans. Pattern Anal. Mach. Intell. 25(12): 1631-1639 (2003) - 2002
- [j5]Kwang In Kim, Jin Hyung Kim, Keechul Jung:
Face Recognition using Support Vector Machines with Local Correlation Kernels. Int. J. Pattern Recognit. Artif. Intell. 16(1): 97-111 (2002) - [j4]Kwang In Kim, Keechul Jung, Se Hyun Park, Hang Joon Kim:
Support Vector Machines for Texture Classification. IEEE Trans. Pattern Anal. Mach. Intell. 24(11): 1542-1550 (2002) - [j3]Kwang In Kim, Keechul Jung, Hang Joon Kim:
Face recognition using kernel principal component analysis. IEEE Signal Process. Lett. 9(2): 40-42 (2002) - [c2]Keechul Jung, Kwang In Kim, JungHyun Han:
Text Scanner with Text Detection Technology on Image Sequences. ICPR (3) 2002: 473-476 - [c1]Kwang In Kim, Keechul Jung, Jin Hyung Kim:
Color Texture-Based Object Detection: An Application to License Plate Localization. SVM 2002: 293-309 - 2001
- [j2]Kwang In Kim, Keechul Jung, Se Hyun Park, Hang Joon Kim:
Support vector machine-based text detection in digital video. Pattern Recognit. 34(2): 527-529 (2001)
1990 – 1999
- 1999
- [j1]Jin Wook Kim, Kwang In Kim, Bong Joon Choi, Hang Joon Kim:
Decomposition of Chinese character into strokes using mathematical morphology. Pattern Recognit. Lett. 20(3): 285-292 (1999)
Coauthor Index
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