3D Canonicalization

3D Canonicalization is a technique in the field of computer vision aimed at estimating a transformation-invariant feature for 3D object classification and part segmentation tasks. This process enhances the consistency and robustness of feature representation by standardizing the pose and position of 3D models, thereby improving the model's recognition capabilities and generalization performance. Its application value lies in enhancing the accuracy of visual understanding in complex 3D scenes and optimizing the performance of machine learning models in real-world environments.