Zi-Yu Liu

MAETrack: Unleashing the Potential of Pretrained Geometric Priors for 3D Single Object Tracking

Large-scale pre-training has transformed representation learning in 2D vision, yet its transferability to 3D single object tracking (SOT) remains insufficiently understood. Directly fine-tuning self-supervised 3D encoders, such as masked autoencoders (MAE), often leads to sub-optimal adaptation because the reconstructi...