349 citations · 701 across the 15 of their papers we have counts for
4 papers · 1 filter
Improving Generalization in Reinforcement Learning with Mixture Regularization
Kaixin Wang, Bingyi Kang, Jie Shao +1
Deep reinforcement learning (RL) agents trained in a limited set of environments tend to suffer overfitting and fail to generalize to unseen testing environments. To improve their…
Few-shot Classification via Adaptive Attention
Zihang Jiang, Bingyi Kang, Kuangqi Zhou +1
Training a neural network model that can quickly adapt to a new task is highly desirable yet challenging for few-shot learning problems. Recent few-shot learning methods mostly con…
The Devil is in Classification: A Simple Framework for Long-tail Object Detection and Instance Segmentation
Tao Wang, Yu Li, Bingyi Kang +5
Most existing object instance detection and segmentation models only work well on fairly balanced benchmarks where per-category training sample numbers are comparable, such as COCO…
Overcoming Classifier Imbalance for Long-tail Object Detection with Balanced Group Softmax
Yu Li, Tao Wang, Bingyi Kang +4
Solving long-tail large vocabulary object detection with deep learning based models is a challenging and demanding task, which is however under-explored.In this work, we provide th…