Foundation models generalize well to various downstream tasks, thanks to their web-scale pre-training, and have become a de-facto tool in pushing the frontiers of computer vision research. Despite the exciting progress, developing foundation models requires large compute resources, incurring heavy environmental costs. For instance, CLIP reports the use of hundreds of GPUs and LLaMA 2 family led to an emission of 539 tCO2eq, requiring about 27,000 trees in one year to capture1 the emissions. It is a pleasure to announce that the first-ever workshop on Green FOundation MOdels (GreenFOMO) has been accepted to be hosted at ECCV 2024. Green FOMO is proposed to accelerate momentum around these emerging research topics, foster an inclusive research and innovation ecosystem involving small/medium sized practitioners in both academia and industry, and collectively making a green impact to society.
This is a joint workshop, a connection of people which recognize that something has to be urgently done.
Here is the team: Yiming Wang (FBK), Subhankar Roy (University of Aberdeen), Massimiliano Mancini (University of Trento), Kaiyang Zhou (Hong kong Baptist University), Enzo Tartaglione (Telecom Paris), Aishwarya Agrawal (University of Montreal), Girmaw Abebe Tadesse (Microsoft),
Marco Cristani (University of Verona), Zeynep Akata (Technical University of Munich).
Website will be published soon!