During the latest edition of the International Conference on Intelligent Robots and Systems (IROS), at the workshop “Long-Term Perception for Autonomy in Dynamic Human-shared Environments: What Do Robots Need?”, our PI Abhinav Valada, along with Daniele Cattaneo, showcased their work titled “Taxonomy-Aware Continual Semantic Segmentation in Hyperbolic Spaces for Open-World Perception”, for which they were awarded the Outstanding Workshop Presentation Award.
This paper, also authored by our doctoral researcher Julia Hindel, introduces TOPICS, a semantic segmentation model that utilizes class-incremental semantic segmentation to update the model with emerging new classes, but unlike the current state-of-the-art methods, it does not constrain features of the new model to imitate those of the prior model, effectively outperforming previous methods both quantitively and qualitatively.
Their work may present a significant advancement in the development of self-driving vehicles, for which comprehensive scene understanding, capable of adequately learning from the new incoming objects of the open world, is a fundamental need.
We congratulate our researchers on this achievement and look forward to their future work in the field of robotics!
Institute of Medical Biometry and Statistics,
Faculty of Medicine and Medical Center –
University of Freiburg
