Zero-shot point cloud semantic segmentation aims to recognize novel classes at the point level. Previous methods mainly transfer excellent zero-shot generalization capabilities from images to point clouds. However, directly transferring knowledge from ...

Emotion recognition has attracted a lot of interest in recent years in various application areas such as healthcare and autonomous driving. Existing approaches to emotion recognition are based on visual, speech, or psychophysiological signals. However, ...

Language Embedded Radiance Fields (LERF) achieves promising results in real-time dense relevancy maps within NeRF 3D scenes. Although LERF shows impressive zero-shot ability in many long-tail open-vocabulary queries, the quality of relevancy maps ...

Traditional 3D segmentation methods can only recognize a fixed range of classes that appear in the training set, which limits their application in real-world scenarios due to the lack of generalization ability. Large-scale visual-language pre-trained ...