Vision and Language: The Past, Present, and Future
Computer vision and natural language processing are two key branches of artificial intelligence. Since the goal of computer vision has always been automatic extraction, analysis, and understanding of useful information from a single image or a sequence of images, it is natural for vision and language to come together to enable high-level computer vision tasks. Conversely, information extracted from images and videos can facilitate natural language processing tasks. Recent advances in machine learning and deep learning are facilitating reasoning about images and text in a joint fashion. in this talk, we will review a recently active area of research at the intersection of vision and language, including video-language alignment, image and video captioning, visual question answering, image retrieval using complex text queries, image generation from textual descriptions, language grounding in images and videos, as well as multimodal machine translation and vision-aided grammar induction.
Jiebo Luo , The University of Rochester.
Jiebo Luo is a Professor of Computer Science at the University of Rochester which he joined in 2011 after a prolific career of fifteen years at Kodak Research Laboratories. He has authored over 500 technical papers and holds over 90 U.S. patents. His research interests include computer vision, NLP, machine learning, data mining, computational social science, and digital health. He has been involved in numerous technical conferences, including serving as program co-chair of ACM Multimedia 2010, IEEE CVPR 2012, ACM ICMR 2016, and IEEE ICIP 2017, and general co-chair of ACM Multimedia 2018. He has served on the editorial boards of the IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), IEEE Transactions on Multimedia (TMM), IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), IEEE Transactions on Big Data (TBD), ACM Transactions on Intelligent Systems and Technology (TIST), Pattern Recognition, Knowledge and Information Systems (KAIS), Machine Vision and Applications, and Intelligent Medicine. He is the current Editor-in-Chief of the IEEE Transactions on Multimedia. Professor Luo is a Fellow of ACM, AAAI, IEEE, SPIE, and IAPR.
Changing Frame Rates and Video Quality
Modern streaming video providers continuously seek to improve consumer experiences by delivering higher-quality, denser content. An important direction that bears study is high-frame rate and changing frame rate (HFR) videos, which present unique problems involving balances between frame rate, video quality, and compression. I will describe new large-scale perceptual studies that we have conducted that are focused on these issues. I will also describe new computational video quality models that address highly practical questions, such as frame rate selection versus compression, and how to combine space-time sampling with compression. My hopes are that these contributions will help further advance the global delivery of HFR and changing frame rate video content.
Alan C. Bovik , The University of Texas at Austin.
Al Bovik is the Cockrell Family Regents Endowed Chair Professor at The University of Texas at Austin. He has received many major international awards, including a 2020 Technology and Engineering Emmy Award from the National Academy of Television Arts and Sciences, the 2019 Progress Medal of the Royal Photographic Society, the 2019 IEEE Fourier Award, the 2017 Edwin H. Land Medal from the Optical Society of America, the 2015 Primetime Emmy Award for Outstanding Achievement in Engineering Development from the Academy of Television Arts and Sciences, and the Norbert Wiener and ‘Sustained Impact’ Awards of the IEEE Signal Processing Society. His is a Fellow of the IEEE, the Optical Society of America, and SPIE. His books include The Handbook of Image and Video Processing, Modern Image Quality Assessment, and The Essential Guides to Image and Video Processing. Al co-founded and was the longest-serving Editor-in-Chief of the IEEE Transactions on Image Processing and created the IEEE International Conference on Image Processing in Austin, Texas, in November 1994.