21 citations · 21 across the 5 of their papers we have counts for
8 papers
Prompt-guided Scene Generation for 3D Zero-Shot Learning
Majid Nasiri, Ali Cheraghian, Townim Faisal Chowdhury +3
Zero-shot learning on 3D point cloud data is a related underexplored problem compared to its 2D image counterpart. 3D data brings new challenges for ZSL due to the unavailability o…
Learning without Forgetting for 3D Point Cloud Objects
Townim Chowdhury, Mahira Jalisha, Ali Cheraghian +1
When we fine-tune a well-trained deep learning model for a new set of classes, the network learns new concepts but gradually forgets the knowledge of old training. In some real-lif…
Zero-Shot Learning on 3D Point Cloud Objects and Beyond
Ali Cheraghian, Shafinn Rahman, Townim F. Chowdhury +2
Zero-shot learning, the task of learning to recognize new classes not seen during training, has received considerable attention in the case of 2D image classification. However, des…
Semantic-aware Knowledge Distillation for Few-Shot Class-Incremental Learning
Ali Cheraghian, Shafin Rahman, Pengfei Fang +3
Few-shot class incremental learning (FSCIL) portrays the problem of learning new concepts gradually, where only a few examples per concept are available to the learner. Due to the…
Transductive Zero-Shot Learning for 3D Point Cloud Classification
Ali Cheraghian, Shafin Rahman, Dylan Campbell +1
Zero-shot learning, the task of learning to recognize new classes not seen during training, has received considerable attention in the case of 2D image classification. However desp…
Mitigating the Hubness Problem for Zero-Shot Learning of 3D Objects
Ali Cheraghian, Shafin Rahman, Dylan Campbell +1
The development of advanced 3D sensors has enabled many objects to be captured in the wild at a large scale, and a 3D object recognition system may therefore encounter many objects…