Computer Vision News - April 2023

6 Research Paper In traditional transformers, positional encoding is global, meaning that when relating to a timeframe, you always relate to its global index in the time series. This approach fixes each frame to a specific point in time, hindering the mixing of motions across different timeframes. However, relative positional encoding can shift sub-motions from the end of the sequence to the beginning and vice versa, enabling greater flexibility and creativity in the animation process. The use of diffusion models in SinMDM can also facilitate various applications at inference time without further training for specific tasks. “ The first and most basic application would be crowd animation , where you want a few animations that look like they’re doing the same thing, but not exactly the same, ” Inbal explains. “ Synthesising motions with our network would windows, like partially overlapping windows, but will take hours, days, or weeks to run them, ” Sigal explains. “ QnA solves this, using partially overlapping windows without a performance problem. The key idea behind QnA is that all those windows learn and share the queries, unlike the traditional attention mechanism. QnA is very successful for the imaging domain, and we’re the first to use it for the motion domain, which is how we get the temporal receptive fields to be smaller. ” Relative positional encoding is also essential to achieving optimal results .