TL;DR: Off-the-shelf text spotting and re-identification models fail in basic off-road racing settings, even more so during muddy events. Making matters worse, there aren't any public datasets to evaluate or improve models in this domain. To this end, we introduce datasets, benchmarks, and methods for the challenging off-road racing setting. In the dynamic world of sports analytics, machine learning (ML) systems play a pivotal role, transforming vast arrays of visual data into actionable insights. These systems are adept at navigating through thousands of photos to tag athletes, enabling fans and participants alike to swiftly locate images of specific racers or moments from events.

The cloud wars are rapidly separating public cloud leaders from the rest of the pack. Where does IBM Corp. stand now in the cloud market? Considering how far behind its public cloud is against Amazon Web Services Inc. and Microsoft Corp. in market share, the technology giant has wisely chosen to step up its focus on hybrid and multicloud management as its next best hope for deep differentiation. At this stage in the development of the cloud economy, it's not clear whether enterprises will adopt multicloud as a long-term architectural end-state, or simply as a way station on the road to reliance on strategic public cloud providers. Nevertheless, the multicloud option is becoming more prominent in enterprise information technology strategies, as we've seen recently in moves by VMware Inc., Cisco Systems Inc. and others in this arena.