The Cambridge ELLIS Unit Seminar Series holds talks by leading researchers in the area of machine learning and AI. Our next speaker for February 2026 will be Silvia Zuffi ( https://imati.cnr.it/mypage.php?idk=PG-2 ). Details of her talk can be found below.

Model-based 3D reconstruction of animals from images enables the estimation of 3D shape and pose within parametric spaces, supporting a wide range of downstream tasks. Yet this problem remains challenging: it requires expressive models that can generalize across the large diversity of animal species. About ten years ago, we introduced SMAL (Skinned Multi-Animal Linear Model), a simple multi-species parametric model that has since been widely adopted to estimate 3D shape and pose directly from visual data. In this talk, I will discuss the limitations of SMAL and present AWOL (Analysis WithOut synthesis using Language), a framework that leverages natural language to steer parametric 3D models and improve controllability. Finally, I will show how synthetic data generated with AWOL can be used to train systems that predict 3D shape and pose across a broad range of animal species.

https://talks.cam.ac.uk/talk/index/243838