18 citations · 73 across the 41 of their papers we have counts for
5 papers · 1 filter
PANDA -- Patch And Distribution-Aware Augmentation for Long-Tailed Exemplar-Free Continual Learning
Siddeshwar Raghavan, Jiangpeng He, Fengqing Zhu
Exemplar-Free Continual Learning (EFCL) restricts the storage of previous task data and is highly susceptible to catastrophic forgetting. While pre-trained models (PTMs) are increa…
Food Image Generation on Multi-Noun Categories
Xinyue Pan, Yuhao Chen, Jiangpeng He +1
Generating realistic food images for categories with multiple nouns is surprisingly challenging. For instance, the prompt "egg noodle" may result in images that incorrectly contain…
Comprehensive Evaluation of Large Multimodal Models for Nutrition Analysis: A New Benchmark Enriched with Contextual Metadata
Bruce Coburn, Jiangpeng He, Megan E. Rollo +3
Large Multimodal Models (LMMs) are increasingly applied to meal images for nutrition analysis. However, existing work primarily evaluates proprietary models, such as GPT-4. This le…
CL-LoRA: Continual Low-Rank Adaptation for Rehearsal-Free Class-Incremental Learning
Jiangpeng He, Zhihao Duan, Fengqing Zhu
Class-Incremental Learning (CIL) aims to learn new classes sequentially while retaining the knowledge of previously learned classes. Recently, pre-trained models (PTMs) combined wi…
Robust3D-CIL: Robust Class-Incremental Learning for 3D Perception
Jinge Ma, Jiangpeng He, Fengqing Zhu
3D perception plays a crucial role in real-world applications such as autonomous driving, robotics, and AR/VR. In practical scenarios, 3D perception models must continuously adapt…