Search Results for author:
Found 3 papers, 2 papers with code
Prompt-Based Exemplar Super-Compression and Regeneration for Class-Incremental Learning
Replay-based methods in class-incremental learning (CIL) have attained remarkable success, as replaying the exemplars of old classes can significantly mitigate catastrophic forgetting.
Evidential Uncertainty Quantification: A Variance-Based Perspective
Uncertainty quantification of deep neural networks has become an active field of research and plays a crucial role in various downstream tasks such as active learning.
Generating Images with 3D Annotations Using Diffusion Models
With explicit 3D geometry control, we can easily change the 3D structures of the objects in the generated images and obtain ground-truth 3D annotations automatically.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
