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REFERENCES

1 
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J. Li, Y. Wong, Q. Zhao and M. S. Kankanhalli, ``Learning to learn from noisy labeled data,'' in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.URL
3 
T.-H. Oh, H. Kim, Y.-W. Tai, J.-C. Bazin and I. S. Kweon, ``Partial Sum Minimization of Singular Values in RPCA for Low-Level Vision,'' in IEEE International Conference on Computer Vision, (ICCV), 2013.URL
4 
T.-H. Oh, Y. Matsushita, Y.-W. Tai and I. S. Kweon, ``Fast Randomized Singular Value Thresholding for Low-rank Optimization,'' IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2018.URL
5 
T.-H. Oh, Y. Matsushita, Y.-W. Tai and I. S. Kweon, ``Fast Randomized Singular Value Thresholding for Nuclear Norm Minimization,'' in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.URL
6 
T.-H. Oh, Y.-W. Tai, J.-C. Bazin, H. Kim and I. S. Kweon, ``Partial Sum Minimization of Singular Values in Robust PCA: Algorithm and Applications,'' IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2016.URL
7 
T.-H. Oh, D. Wipf, Y. Matsushita and I. S. Kweon, ``A Pseudo-Bayesian Algorithm for Robust PCA,'' in Neural Information Processing Systems (NeurIPS), 2016.URL
8 
D. Acuna, H. Ling, A. Kar and S. Fidler, ``Efficient Annotation of Segmentation Datasets with Polygon-RNN++,'' in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.URL
9 
T.-H. Oh, R. Jaroensri, C. Kim, M. Elgharib, F. Durand and W. T. Freeman, ``Learning-based Video Motion Magnification,'' in European Conference on Computer Vision (ECCV), 2018.URL
10 
A. Kaspar, T.-H. Oh, L. Makatura, P. Kellnhofer, J. Aslarus and W. Matusik, ``Neural Inverse Knitting: From Images to Manufacturing Instructions,'' in International Conference on Machine Learning (ICML), 2019.URL
11 
M. B. R., A. Tewari, T.-H. Oh, T. Weyrich, B. Bickel, H.-P. Seidel, H. Pfister, W. Matusik, M. Elgharib and C. Theobalt, ``Monocular Reconstruction of Neural Face Reflectance Fields,'' in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021.URL
12 
D.-J. Kim, J. Choi, T.-H. Oh and I. S. Kweon, ``Dense Relational Captioning: Triple-Stream Networks for Relationship-Based Captioning,'' in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.URL
13 
M. Oquab, L. Bottou, I. Laptev and J. Sivic, ``Learning and Transferring Mid-Level Image Representations using Convolutional Neural Networks,'' in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014.URL
14 
J. Choi, T.-H. Oh and I. S. Kweon, ``Contextually Customized Video Summaries via Natural Language,'' in IEEE Winter Conference on Applications of Computer Vision (WAVC), 2018.URL
15 
Z. Li and D. Hoiem, ``Learning without forgetting,'' IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017.URL
16 
D.-J. Kim, J. Choi, T.-H. Oh, Y. Yoon and I. S. Kweon, ``Disjoint Multi-task Learning between Heterogeneous Human-centric Tasks,'' in IEEE Winter Conference on Applications of Computer Vision (WAVC), 2018.URL
17 
A. Senocak, T.-H. Oh, J. Kim, M.-H. Yang and I. S. Kweon, ``Learning to Localize Sound Source in Visual Scenes,'' in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.URL
18 
A. Senocak, T.-H. Oh, J. Kim, M.-H. Yang and I. S. Kweon, ``Learning to Localize Sound Sources in Visual Scenes: Analysis and Applications,'' IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020.URL
19 
R. Gao, T.-H. Oh, K. Grauman and L. Torresani, ``Listen to Look: Action Recognition by Previewing Audio,'' in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020.URL
20 
T.-H. Oh, T. Dekel, C. Kim, I. Mosseri, W. T. Freeman, M. Rubinstein and W. Matusik, ``Speech2Face: Learning the Face Behind a Voice,'' in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.URL
21 
S. Lee, J. Kim, T.-H. Oh, Y. Jeong, D. Yoo, S. Lin and I. S. Kweon, ``Visuomotor Understanding for Representation Learning of Driving Scenes,'' in The British Machine Vision Conference (BMVC), 2019.URL
22 
I. Shim, T.-H. Oh and I. S. Kweon, ``High-fidelity Depth Upsampling using Self-learning Framework,'' MDPI Sensors, 2019.URL
23 
D. Kim, K. Saito, T.-H. Oh, B. A. Plummer, S. Sclaroff and K. Saenko, ``CDS: Cross-Domain Self-supervised Pre-training,'' in IEEE International Conference on Computer Vision, (ICCV), 2021.URL
24 
J. Kim, T.-H. Oh, S. Lee, F. Pan and I. S. Kweon, ``Variational Prototyping-Encoder: One-Shot Learning with Prototypical Images,'' in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.URL
25 
D.-J. Kim, J. Choi, T.-H. Oh and I. S. Kweon, ``Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach,'' in Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019.URL
26 
D. Cho, J. Park, T.-H. Oh, Y.-W. Tai and I. S. Kweon, ``Weakly- and Self-Supervised Learning for Content-aware Deep Image Retargeting,'' in IEEE International Conference on Computer Vision, (ICCV), 2017.URL
27 
Y. Aksoy, T.-H. Oh, S. Paris, M. Pollefeys and W. Matusik, ``Semantic Soft Segmentation,'' ACM Transactions on Graphics (ACM SIGGRAPH), 2018.URL
28 
J. Kim, S. Lee, T.-H. Oh and I. S. Kweon, ``Co-domain Embedding using Deep Quadruplet Network for Unseen Traffic Sign Recognition,'' in AAAI Conference on Artificial Intelligence (AAAI), 2018.URL
29 
K. Byung-Ki, N. Hyeon-Woo, and T.-H. Oh, ``DFlow: Learning to Synthesize Better Optical Flow Datasets via a Differentiable Pipeline,'' in International Conference on Learning Representations (ICLR), 2023.URL
30 
N. Hyeon-Woo, M. Ye-Bin, and T.-H. Oh, ``FedPara: Low-rank Hadamard Product for Communication-Efficient Federated Learning,'' in International Conference on Learning Representations (ICLR), 2022.URL
31 
K. Youwang, K. Ji-Yeon, and T.-H. Oh, ``CLIP-Actor: Text-Driven Recommendation and Stylization for Animating Human Meshes,'' in European Conference on Computer Vision (ECCV), 2022.URL
32 
K. Jun-Seong, K. Yu-Ji, M. Ye-Bin, and T.-H. Oh, ``HDR- Plenoxels: Self-Calibrating High Dynamic Range Radiance Fields,'' in European Conference on Computer Vision (ECCV), 2022.URL
33 
J. Cho, K. Youwang, and T.-H. Oh, ``Cross-Attention of Disentangled Modalities for 3D Human Mesh Recovery with Transformers,'' in European Conference on Computer Vision (ECCV), 2022.URL
34 
B. Han, T.-H. Oh, ``Learning Few-shot Segmentation from Bounding Box Annotations,'' in IEEE Winter Conference on Applications of Computer Vision (WACV), 2023.URL
35 
A. Senocak, J. Kim, T.-H. Oh, D. Li, and I. S. Kwon, ``Event-Specific Audio-Visual Fusion Layers: A Simple and New Perspective on Video Understanding,'' in IEEE Winter Conference on Applications of Computer Vision (WACV), 2023.URL
36 
K. Sung-Bin, A. Senocak, H. Hyunwoo, A.Owens, and T.-H. Oh, ``Sound to Visual Scene Generation by Audio-to-Visual Latent Alignment,'' in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.URL
37 
M. Ye-Bin, D. Choi, Y. Kwon, J. Kim, and T.-H. Oh ``ENInst: Enhancing Weakly-supervised Low-shot Instance Segmentation,'' in Pattern Recognition (2023).URL
38 
M. Kim, K. Sung-Bin, and T.-H. Oh, ``Prefix Tuning for Automated Audio Captioning,'' International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2023.URL
39 
S.-E. Lee, S.-E. Choi, G. Park, Y.-Y. Kang, J.-W. Baek, and K. Chung, ``Mask R-CNN-based Occlusion Anomaly Detection Considering Orientation in Manufacturing Process Data,'' in IEIE Transactions on Smart Processing and Computing (IEIESPC), Vol. 11, No. 06, p. 393-399, 2022.URL
40 
S.-M. Woo, S.-E. Lee, and J.-O. Kim, ``Deep Texture-adaptive Image Denoising for Practical Application,'' in IEIE Transactions on Smart Processing and Computing (IEIESPC), Vol. 11, No. 06, p. 412-420, 2022.URL
41 
J. Kim, S. Kim, C. Pyo, H. Kim, and C. Yim, ``Progressive Dehazing and Depth Estimation from a Single Hazy Image,'' in IEIE Transactions on Smart Processing and Computing (IEIESPC), Vol. 11, No. 05, p. 343-350, 2022.URL
42 
Y. Seo, J. Lee, U. Sunarya, K. Lee, and C. Park, ``Continuous Blood Pressure Estimation using 1D Convolutional Neural Network and Attention Mechanism,'' in IEIE Transactions on Smart Processing and Computing (IEIESPC), Vol. 11, No. 03, p. 169-173, 2022.URL
43 
A. Krizhevsky, I. Sutskever, and G. E. Hinton, ``ImageNet Classification with Deep Convolutional Neural Networks,'' in Advances in Neural Information Processing Systems, 2012.URL
44 
K. Byung-Ki, K. Sung-Bin, T.-H. Oh, ``The Devil in the Details: Simple and Effective Optical Flow Synthetic Data Generation,'' in arXiv preprint arXiv:2308.07378, 2023.DOI
45 
M. Ye-Bin, N. Hyeon-Woo, W. Choi, N. Kim, S. Kwak, T.-H. Oh, ``Exploiting Synthetic Data for Data Imbalance Problems: Baselines from a Data Perspective,'' in arXiv preprint arXiv:2308.00994, 2023.DOI
46 
G. Auda, M. Kamel, ``Modular neural networks: a survey,'' in International Journal of Neural Systems, Vol. 9, No. 02, 129-151, 1999.DOI
47 
K. Youwang, K. Ji-Yeon, K. Joo, T.-H. Oh, ``Unified 3D Mesh Recovery of Humans and Animals by Learning Animal Exercise,'' in The British Machine Vision Conference (BMVC), 2021.DOI
48 
M. Ye-Bin, J. Kim, H. Kim, K. Son, T.-H. Oh, ``TextManiA: Enriching Visual Feature by Text-driven Manifold Augmentation,'' in IEEE International Conference on Computer Vision, (ICCV), 2023.DOI
49 
S. Park, M. Song, B. Kim, T.-H. Oh, ``Unsupervised Pre-Training for Data-Efficient Text-to-Speech on Low Resource Languages,'' in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023.DOI
50 
D. J. Kim, T.-H. Oh, J. Choi, I. S. Kweon, ``Dense relational image captioning via multi-task triple-stream networks,'' in IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(11), 7348-7362, 2021.DOI