20 citations · 68 across the 8 of their papers we have counts for
8 papers · 1 filter
SLCA: Slow Learner with Classifier Alignment for Continual Learning on a Pre-trained Model
Gengwei Zhang, Liyuan Wang, Guoliang Kang +2
The goal of continual learning is to improve the performance of recognition models in learning sequentially arrived data. Although most existing works are established on the premis…
Mask Matching Transformer for Few-Shot Segmentation
Siyu Jiao, Gengwei Zhang, Shant Navasardyan +4
In this paper, we aim to tackle the challenging few-shot segmentation task from a new perspective. Typical methods follow the paradigm to firstly learn prototypical features from s…
Continual Object Detection via Prototypical Task Correlation Guided Gating Mechanism
Binbin Yang, Xinchi Deng, Han Shi +6
Continual learning is a challenging real-world problem for constructing a mature AI system when data are provided in a streaming fashion. Despite recent progress in continual class…
NASOA: Towards Faster Task-oriented Online Fine-tuning with a Zoo of Models
Hang Xu, Ning Kang, Gengwei Zhang +3
Fine-tuning from pre-trained ImageNet models has been a simple, effective, and popular approach for various computer vision tasks. The common practice of fine-tuning is to adopt a…
Loss Function Discovery for Object Detection via Convergence-Simulation Driven Search
Peidong Liu, Gengwei Zhang, Bochao Wang +4
Designing proper loss functions for vision tasks has been a long-standing research direction to advance the capability of existing models. For object detection, the well-establishe…
Ada-Segment: Automated Multi-loss Adaptation for Panoptic Segmentation
Gengwei Zhang, Yiming Gao, Hang Xu +3
Panoptic segmentation that unifies instance segmentation and semantic segmentation has recently attracted increasing attention. While most existing methods focus on designing novel…