2018 - Fellow of the Royal Academy of Engineering (UK)
2017 - Member of the National Academy of Engineering For contributions to computer vision and computer graphics, and for leadership in industrial research and product development.
2006 - ACM Fellow For contributions to computer vision and computer graphics.
2006 - IEEE Fellow For contributions to image-based modeling and rendering.
His primary scientific interests are in Artificial intelligence, Computer vision, Computer graphics, Image processing and Pattern recognition. In his work, Heung-Yeung Shum performs multidisciplinary research in Artificial intelligence and Set. His is doing research in Rendering, Pixel, Image, Image-based modeling and rendering and Image restoration, both of which are found in Computer vision.
His work on 3D computer graphics and Three dimensional television as part of general Computer graphics study is frequently linked to Transformation matrix and Virtual travel, therefore connecting diverse disciplines of science. His Image processing study also includes fields such as
Heung-Yeung Shum mainly focuses on Artificial intelligence, Computer vision, Computer graphics, Rendering and Pattern recognition. His Artificial intelligence study is mostly concerned with Image, Iterative reconstruction, Image texture, Image segmentation and Pixel. His research on Computer vision often connects related areas such as Computer graphics.
His research ties Interpolation and Computer graphics together. Heung-Yeung Shum has researched Rendering in several fields, including Concentric and Displacement mapping. Heung-Yeung Shum interconnects Facial recognition system and Face detection in the investigation of issues within Pattern recognition.
His primary areas of investigation include Artificial intelligence, Computer vision, Rendering, Computer graphics and Information retrieval. Heung-Yeung Shum has included themes like Natural language processing and Pattern recognition in his Artificial intelligence study. His Image-based modeling and rendering, Image texture, Image retrieval, Image and Feature extraction investigations are all subjects of Computer vision research.
His Rendering study also includes
His scientific interests lie mostly in Artificial intelligence, Computer vision, Information retrieval, Pattern recognition and Chatbot. His study in Image gradient, Image restoration, Iterative reconstruction, Image texture and Image is done as part of Artificial intelligence. His work carried out in the field of Image texture brings together such families of science as Algorithm and Texture mapping.
His research on Computer vision often connects related topics like Interpolation. His biological study spans a wide range of topics, including Facial recognition system, Cognitive neuroscience of visual object recognition and Image retrieval. His work deals with themes such as Markov decision process and Human–computer interaction, which intersect with Chatbot.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Learning to Detect a Salient Object
Tie Liu;Zejian Yuan;Jian Sun;Jingdong Wang.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2011)
Learning to Detect A Salient Object
Tie Liu;Jian Sun;Nan-Ning Zheng;Xiaoou Tang.
computer vision and pattern recognition (2007)
Stereo matching using belief propagation
Jian Sun;Nan-Ning Zheng;Heung-Yeung Shum.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2003)
Yin Li;Jian Sun;Chi-Keung Tang;Heung-Yeung Shum.
international conference on computer graphics and interactive techniques (2004)
Creating full view panoramic image mosaics and environment maps
Richard Szeliski;Heung-Yeung Shum.
international conference on computer graphics and interactive techniques (1997)
Real-time texture synthesis by patch-based sampling
Lin Liang;Ce Liu;Ying-Qing Xu;Baining Guo.
ACM Transactions on Graphics (2001)
Jin-Xiang Chai;Xin Tong;Shing-Chow Chan;Heung-Yeung Shum.
international conference on computer graphics and interactive techniques (2000)
Image super-resolution using gradient profile prior
Jian Sun;Zongben Xu;Heung-Yeung Shum.
computer vision and pattern recognition (2008)
Image deblurring with blurred/noisy image pairs
Lu Yuan;Jian Sun;Long Quan;Heung-Yeung Shum.
international conference on computer graphics and interactive techniques (2007)
Image segmentation by data driven Markov chain Monte Carlo
Zhuowen Tu;Song-Chun Zhu;Heung-Yeung Shum.
international conference on computer vision (2001)
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