BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:Cross-Species 3D Animal Model-Based Reconstruction - Silvia Zuffi\
 , IMATI\, Italian National Research Council
DTSTART:20260203T150000Z
DTEND:20260203T160000Z
UID:TALK243838@talks.cam.ac.uk
CONTACT:Elliott Wu
DESCRIPTION:Model-based 3D reconstruction of animals from images enables t
 he 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 s
 ince been widely adopted to estimate 3D shape and pose directly from visua
 l data. In this talk\, I will discuss the limitations of SMAL and present 
 AWOL (Analysis WithOut synthesis using Language)\, a framework that levera
 ges natural language to steer parametric 3D models and improve controllabi
 lity. 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.\n\n\nBio of Speaker:\nSilvia Zuffi is a Senior Research
  Scientist at the IMATI (Institute of Applied Mathematics and Information 
 Technologies) of the Italian National Research Council (CNR) in Milan. She
  holds a PhD in Computer Science from Brown University\, where her thesis 
 focused on “Shape models of the human body for distributed inference” 
 under the supervision of Prof. Michael J. Black. Her academic background a
 lso includes a Master of Science in Computer Science from Brown University
  and a degree in Electronic Engineering from the University of Bologna. Sh
 e held also a postdoctoral position at the Perceiving Systems group of the
  Max Planck Institute for Intelligent Systems (Tübingen\, Germany).\nHer 
 research lies at the intersection of computer vision\, graphics\, and mach
 ine learning\, with a special emphasis on pose and shape estimation for hu
 mans and animals from images and video data. Over her career\, she has con
 tributed to realistic modeling of articulated bodies\, and the development
  of generative models for animal 3D shape and pose reconstruction. Her ear
 lier work includes research in color imaging\, multispectral imaging\, and
  visual perception.\nSilvia’s ongoing projects address challenges in rec
 onstructing 3D shape and pose of animals from “in the wild” imagery\, 
 contributing tools for applications in ecology\, conservation\, animal wel
 lness and visual computing.
LOCATION:LT6\, Department of Engineering\; Zoom: https://cam-ac-uk.zoom.us
 /j/89905399582?pwd=ap5btgYWVX6lb9lyx7RGW58pGzGavX.1
END:VEVENT
END:VCALENDAR