Selected Journal Papers

  1. C.C. Hsu, C.H. Lin, C.-H. Kao, and Y.-C. Lin, “DCSN: Deep compressed sensing network for efficient hyperspectral data transmission of miniaturized satellite,” IEEE Transactions on Geoscience and Remote Sensing (IF: 5.85, Rank 29/1409=2% in Electrical and Electronic Engineering), 2020 (accepted).
  2. C.C. Hsu, Y.X. Cheung, C.Y. Lee, “Deep Fake Image Detection based on Pairwise Learning,” Applied Sciences (SCI/Q2), 10(1), 370, Jan. 2020. (IF: 2.21, Rank 85/299=28% in General Engineering)
  3. C.C. Hsu, C.W. Lin, W.T. Su, and G. Cheung, “SiGAN: Siamese generative adversarial network for identity-preserving face hallucination,” IEEE Transactions on Image Processing (TIP), vol. 28, issue 12, pp. 6225-6236, Dec. 2019. (IF:9.34, Rank: 5/334=1% in Computer Graphics and Computer-Aided Design Software).
  4. C.C. Hsu, C.W. Lin, “CNN-Based Joint Clustering and Representation Learning with Feature Drift Compensation for Large-Scale Image Data,” IEEE Transactions on Multimedia (TMM), vol. 20, issue 2, pp. 421-429 , Feb. 2018. (IF:6.051, Rank: 2/195=1% in Media Technology).
  5. W. Kang, C.C. Hsu, B.Q. Zhuang, C.W. Lin, and C.H. Yeh, “Learning-based joint super-resolution and deblocking for a highly compressed image,” IEEE Transactions on Multimedia (TMM), vol. 17, issue. 7,  pp. 921−934, July 2015 (IF: 6.051, Ranking: 2/195=1% in Media Technology).
  6. C.C. Hsu, L.W. Kang, and C.W. Lin, “Temporally coherent super-resolution of textured video via dynamic texture synthesis,” IEEE Transaction on Image Processing (TIP),vol. 24, issue. 3, pp.919-931, March 2015 (IF:9.34, Rank: 5/334=1% in Computer Graphics and Computer-Aided Design Software).
  7. C.C. Hsu,C.W Lin, Y. Fan, and W. Lin, “Objective quality assessment for image retargeting based on perceptual geometric distortion and information loss,” IEEE Journal on Selected Topics in Signal Processing (Special Issue on Perception Inspired Video Processing), vol. 8, issue 3, pp. 377-389, June 2014 (IF:4.981, Rank: 7/543=1% in Signal Processing).

Book Chapters

  1. H.T. Chang and C.C. Hsu, “Fractal-based Secured multiple-image distribution and compression,” in Handbook of Research on Secure Multimedia Distribution, Chapter 27, Edited by Dr. Shiguo Lian and Dr. Yan Zhang, ISBN: 978-1-60566-262-6, 2008.

Selected Conference Papers

  1. C.C. Hsu, W.H. Zheng, H.T. Yang, C.H. Lin, and C.H. Kao, “Rethinking Relation between Model Stacking and Recurrent Neural Networks for Social Media Prediction,” in Proc. of ACM Multimedia, 12-16 Oct. 2020 (Oral).
  2. C.C. Hsu, W.H. Zheng, and H.T. Yang, “Learning to Predict Risky Driving Behaviors for Autonomous Driving,” in Proc. IEEE International Conference on Consumer Electronics – Taiwan (ICCE-TW), 28-30 Sept. 2020.
  3. C.C. Hsu and K.Y. Huang, “Coupled adversarial learning for single image super-resolution,” in Proc. IEEE Sensor Array and Multichannel Signal Processing Workshop (IEEE SAM), June 2020.
  4. C.C. Hsu, C.H. Hung, C.Y. Jian,, “Stronger baseline for vehicle re-identification in the wild,” in Proc. IEEE Conf. Visual Communication and Image Processing (VCIP), Dec. 2019.
  5. C.C. Hsu and C.H. Lin, “Dual reconstruction with densely connected residual network for single image super-resolution,” in Proc. IEEE International Conference on Computer Vision (ICCV, Top Conference on Computer Vision) Workshop, Oct. 2019.
  6. C.C. Hsu, L.W. Kang, C.Y. Lee,, ” Popularity prediction of social media based on multi-modal feature mining,” ACM Multimedia (ACM MM, Top Conference on Multimedia), Nice, France, 21 – 25 Oct. 2019.
  7. X. Zhuang and C.C. Hsu, “Detecting generated image based on coupled network with two-step pairwise learning,” IEEE International Conference on Image Processing (ICIP, Top Conference on Multimedia), Taipei, Taiwan, 2019. (Best Student Award)
  8. C.C. Hsu, C.Y. Lee, Y.X. Cheung, “Learning to detect fake face images in the wild,”International Symposium on Computer, Consumer and Control (IS3C), pp. 388-391, Taichung, Taiwan, 2018.
  9. C.C. Hsu, C.Y. Lee, T.X. Liao,, “An iterative refinement approach for social media headline prediction,” ACM Multimedia (ACM MM), Seoul, Korea, 22 – 26 Oct. 2018.
  10. W.-T. Su, C.C. Hsu, Z. Huang, C.W. Lin, G. Cheung, “Joint pairwise learning and image clustering based on a siamese CNN, ” IEEE International Conference on Image Processing (ICIP), Athens, Greece, Oct. 7-10, 2018.
  11. C.C. Hsu and C.W. Lin, “Objective quality assessment for video retargeting based on spatio-temporal distortion analysis,” IEEE Conference on Visual Communications and Image Processing (VCIP), 10-13 Dec. 2017. (Oral).
  12. C.C. Hsu, Yi-Jin Lee, Pei-An Lu, Shan-Shin Lu, et. al. “Social media popularity prediction based on random forest and residual learning,” ACM Multimedia (ACM MM), Mountain View, CA, USA, Oct. 2017. (Oral & Best Grand Challenge Paper Award)
  13. C.C. Hsu and C.W. Lin, “Unsupervised convolutional neural networks for large-scale image clustering,” IEEE International Conference on Image Processing (ICIP), Beijing, China, September 2017.
  14. W. Kang, B.C. Chuang,C.C. Hsu, C.W. Lin, and C.H. Yeh, “Self-Learning-Based Single Image Super-Resolution of a Highly Compressed Image,” IEEE Workshop Multimedia Signal Processing (MMSP), Sept. 2013, Sardinia, Italy. (Top 10% Paper Award)


  1. C. Hsu and T.C. Lee, “System and method for diagnosing gastrointestinal neoplasm,” US Patent (Enclosing publication)
  2. 童曉儒, 許志仲, 張文誠, “影像辨識方法”, Taiwan Patent, 2018.
  3. 許志仲與張軒韶,”影像辨識系統及其操作方法,” Taiwan Patent #201329874, 2013.
  4. 許志仲與林嘉文,”利用仿射轉換建立影像資料庫之方法,” Taiwan Patent #201317938, 2013.
  5. Chih-Chung Hsu and Chia-Wen Lin, “Method and system for example-based face hallucination,” USA patent # 8,488,913, 2013.
  6. Chih-Chung Hsu and Chia-Wen Lin, “Super-resolution method and system for human face based on sample,” China patent #CN102298775 B, 2013.
  7. 林嘉文與許志仲,”以樣本為基礎之人臉超解析度方法與系統,” Taiwan Patent #201145181, 2011.
  8. 張廷政, 張軒庭, 與許志仲, “應用於網際網路上之分散式並聯加密方法,” Taiwan Patent #094122766, 2005.
  9. 許志仲, 王焜潔, 與張廷政, “應用於網際網路上之分散式加密方法,” Taiwan Patent #093135605, 2004.