PhD Seminar • Computer Vision • Efficient Multi-frame 3D Semantic Segmentation

Please note: This PhD seminar will take place online.

Chengjie Huang, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Krzysztof Czarnecki

We introduce MFSeg, an efficient multi-frame 3D semantic segmentation framework. By aggregating point cloud sequences at the feature level and regularizing the feature extraction and aggregation process, MFSeg reduces computational overhead while maintaining high accuracy. Moreover, by employing a lightweight MLP-based point decoder, our method eliminates the need to upsample redundant points from past frames. Experiments on the nuScenes and Waymo datasets show that MFSeg consistently outperforms existing methods, demonstrating its effectiveness and efficiency.

Attend this PhD seminar virtually on MS Teams