The BEDLAM2.0 dataset (B2) is here, just in time to train your 3D human pose and shape estimation methods for CVPR. B2 goes beyond BEDLAM (B1) to include widely varied and natural camera motions and fields of view, more diverse body shapes, strand-based hair, more garments, shoes, more body motions, and more 3D scenes. Compared with B1, training on B2 produces more accurate 3D human pose, resulting in SOTA accuracy, particularly for estimates in world coordinates. B2 lets you jointly train camera motion and human motion regressors, and we also provide depth maps. Check out bedlam2.is.tuebingen.mpg.de/… data, code, dataset statistics, and much more. BEDLAM2.0 will appear in the 2025 NeurIPS Datasets and Benchmarks Track. Joint work with Joachim Tesch, @gfgbec, Prerana Achar, @AYiannakidis, @mkocab_, @PriyankaP1201.

SMPL is 10 years old and has done what we hoped — it changed the way the field estimates and models 3D humans and their motion. I’m delighted that the original team has been recognized today at @ICCVConference with the Mark Everingham Prize. The prize is given to individuals or teams who have worked to further progress in the computer vision community as a whole. Mark Everingham understood that to have an impact, it is not enough to simply publish a paper. SMPL’s success is due to lots of hard work to provide the community with code, data, and support. My deepest thanks go out to all the members of the @PerceivingSys department who have supported SMPL and related technology over the years. It has been a team effort of many dedicated people and we share this award with you. Mark understood that big changes require community effort. Consequently my big thanks go to all the users of SMPL and related tools. You have pushed the field forward as a community in ways that no small team could. I’m constantly inspired by your work. Computer vision has changed a lot in 10 years but people keep finding new uses for SMPL, most recently in training humanoid robots. There are many more applications to come in games, interactive entertainment, sports, and biomechanics. Congratulations to my coauthors Matt Loper, @naureenmahmood, Javier Romero and @GerardPonsMoll1. smpl.is.tue.mpg.de