To solve the above issues, we propose AutoGPart, a generic method enabling training generalizable 3D part segmentation networks with the task prior considered.
Neural Radiance Field (NeRF) has achieved outstanding performance in modeling 3D objects and controlled scenes, usually under a single scale.
The task of searching certain people in videos has seen increasing potential in real-world applications, such as video organization and editing.
Shots are key narrative elements of various videos, e. g. movies, TV series, and user-generated videos that are thriving over the Internet.
Scene, as the crucial unit of storytelling in movies, contains complex activities of actors and their interactions in a physical environment.
We propose an efficient method to generate white-box adversarial examples to trick a character-level neural classifier.