1 citations · 3 across the 15 of their papers we have counts for
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Unlocking Prototype Potential: An Efficient Tuning Framework for Few-Shot Class-Incremental Learning
Shengqin Jiang, Xiaoran Feng, Yuankai Qi +6
Few-shot class-incremental learning (FSCIL) seeks to continuously learn new classes from very limited samples while preserving previously acquired knowledge. Traditional methods of…
Teaching Prompts to Coordinate: Hierarchical Layer-Grouped Prompt Tuning for Continual Learning
Shengqin Jiang, Tianqi Kong, Yuankai Qi +5
Prompt-based continual learning methods fine-tune only a small set of additional learnable parameters while keeping the pre-trained model's parameters frozen. It enables efficient…
Self-Supervised Cross-Modal Learning for Image-to-Point Cloud Registration
Xingmei Wang, Xiaoyu Hu, Chengkai Huang +4
Bridging 2D and 3D sensor modalities is critical for robust perception in autonomous systems. However, image-to-point cloud (I2P) registration remains challenging due to the semant…
Modeling Pedestrian Intrinsic Uncertainty for Multimodal Stochastic Trajectory Prediction via Energy Plan Denoising
Yao Liu, Quan Z. Sheng, Lina Yao
Pedestrian trajectory prediction plays a pivotal role in the realms of autonomous driving and smart cities. Despite extensive prior research employing sequence and generative model…