Workshop on Robust Recognition in the Open World

at the British Machine Vision Conference (BMVC) 2024

When a recognition AI, realized by a deep neural network (DNN), faces the open world, it will inevitably deal with unexpected scenes. This includes unknown objects and unknown environments / domains that are out of distribution (OOD) with respect to the data encountered during training. DNNs typically suffer from significant degradation of performance when facing OOD objects or domain shifts. This can be seen as the main obstacle for the application of AI-driven perception in medicine, automated driving and open world robotics.

With the advent of vision transformers, large-scale foundation models and vision-language models, a new perspective towards significant progress on this set of problems arises. We invite researchers to submit their original or previously published works on methods and datasets that study and expand the capabilities of DNNs for recognition in an open world.

Join us on 27-28 November 2024 in shaping the future of AI-driven computer vision. We are looking forward to your innovative contributions.

Speakers

Tentative Schedule

Workshop Date: 27-28 November 2024

Time Topic
9:00 - 9:15 Welcome
9:15 - 9:50 Robust Recognition with Image Decomposition – Jiri Matas
9:50 - 10:25 Plenary 2 – Petra Bevandic
10:25 - 10:45 Contributed talks 1-2
Short break
11:00 - 12:00 Contributed talks 3-8
Lunch break
13:30 - 14:00 Contributed talks 9-11
14:00 – 14:45 Challenge session – OOD tracking on videos
14:45 – 15:30 Poster session
Short break
15:40 - 16:15 What is the best paradigm to robustly recognize objects under challenging circumstances – Robert Geirhos
16:15 – 16:50 Plenary 4 – Toby Breckon
16:50 - 17:20 Best paper award, wrap up and closing remarks

Challenge

For this workshop, we invite participants to tackle the challenge of Open-World Object Detection and Tracking. Develop AI models that excel in detecting and tracking objects in diverse and unpredictable environments, addressing out-of-distribution (OOD) objects and domain shifts.

Organizers

Hermann Blum

Hermann Blum

Hanno Gottschalk

Hanno Gottschalk

Kira Maag

Kira Maag

Matthias Rottmann

Matthias Rottmann

Siniša Šegvić

Siniša Šegvić