TY - GEN
T1 - EMCLR’24
T2 - 1st International Workshop on Efficient Multimedia Computing under Limited Resources, EMCLR 2024
AU - Guo, Jinyang
AU - Chen, Zhenghao
AU - Ma, Yuqing
AU - Liu, Xianglong
AU - Kim, Jinman
AU - Ouyang, Wanli
AU - Tao, Dacheng
N1 - Publisher Copyright:
© 2024 Copyright held by the owner/author(s).
PY - 2024/10/28
Y1 - 2024/10/28
N2 - Cutting-edge multimedia computing techniques, especially those recognized for their large-scale capabilities, have exhibited impressive achievements in diverse fields such as computer vision, natural language processing, and speech recognition. However, the significant reliance on vast amounts of data, label, and computational resources of these multimedia computing techniques present challenges when deploying to real-world scenarios with limited resources. This workshop aims to bring together experts in data-efficient, label-efficient, and computation-efficient multimedia computing fields, establishing a collaborative platform to exchange recent breakthroughs and deliberate on the future direction of multimedia computing models. By facilitating the exchange of ideas and insights, we aspire to address the efficiency challenges inherent in multimedia computing and contribute to the evolution of its practical applications in the real world.
AB - Cutting-edge multimedia computing techniques, especially those recognized for their large-scale capabilities, have exhibited impressive achievements in diverse fields such as computer vision, natural language processing, and speech recognition. However, the significant reliance on vast amounts of data, label, and computational resources of these multimedia computing techniques present challenges when deploying to real-world scenarios with limited resources. This workshop aims to bring together experts in data-efficient, label-efficient, and computation-efficient multimedia computing fields, establishing a collaborative platform to exchange recent breakthroughs and deliberate on the future direction of multimedia computing models. By facilitating the exchange of ideas and insights, we aspire to address the efficiency challenges inherent in multimedia computing and contribute to the evolution of its practical applications in the real world.
KW - Efficient methods
KW - artificial intelligence
KW - multimedia computing
UR - https://www.scopus.com/pages/publications/85210869286
U2 - 10.1145/3688863.3696341
DO - 10.1145/3688863.3696341
M3 - 会议稿件
AN - SCOPUS:85210869286
T3 - EMCLR 2024 - Proceedings of the 1st International Workshop on Efficient Multimedia Computing under Limited Resources, Co-Located with: MM 2024
SP - 1
EP - 2
BT - EMCLR 2024 - Proceedings of the 1st International Workshop on Efficient Multimedia Computing under Limited Resources, Co-Located with
PB - Association for Computing Machinery, Inc
Y2 - 28 October 2024 through 1 November 2024
ER -