Although she has no plans to extend this work herself, Sophia is optimistic when asked if it opens new avenues for research. “I think applying this pre-training with more data could be interesting,” she tells us. “Like bigger datasets without any annotations. Then afterwards, finetune the same network with, for example, the nuScenes dataset that we use with annotations for segmentation.” Reflecting on the challenges faced during the project, Sophia shared that it was her first paper and her first research work in machine learning. “It was a challenge in itself leading a research project,” she reveals. “Also, training so many models and testing so many things, that was a challenge.” She noted that the solutions came through persistence and trying new things, as well as the invaluable support of her peers. “I had a very good team of advisors,” she smiles. “I was an intern then, but my fellow PhD students were also helping.” On the broader question of the current state of autonomous driving, which has seen significant technological progress in recent years but continues to face challenges, Sophia acknowledges 20 DAILY CVPR Friday Workshop Poster UKRAINE CORNER Performance comparison in low data regime 1% annotated data of nuScenes.
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