194 citations · 679 across the 30 of their papers we have counts for
8 papers · 1 filter
RSG: A Simple but Effective Module for Learning Imbalanced Datasets
Jianfeng Wang, Thomas Lukasiewicz, Xiaolin Hu +2
Imbalanced datasets widely exist in practice and area great challenge for training deep neural models with agood generalization on infrequent classes. In this work, wepropose a new…
Convolutional Neural Networks with Gated Recurrent Connections
Jianfeng Wang, Xiaolin Hu
The convolutional neural network (CNN) has become a basic model for solving many computer vision problems. In recent years, a new class of CNNs, recurrent convolution neural networ…
End-to-End Semi-Supervised Object Detection with Soft Teacher
Mengde Xu, Zheng Zhang, Han Hu +5
This paper presents an end-to-end semi-supervised object detection approach, in contrast to previous more complex multi-stage methods. The end-to-end training gradually improves ps…
Compressing Visual-linguistic Model via Knowledge Distillation
Zhiyuan Fang, Jianfeng Wang, Xiaowei Hu +3
Despite exciting progress in pre-training for visual-linguistic (VL) representations, very few aspire to a small VL model. In this paper, we study knowledge distillation (KD) to ef…
DAP: Detection-Aware Pre-training with Weak Supervision
Yuanyi Zhong, Jianfeng Wang, Lijuan Wang +3
This paper presents a detection-aware pre-training (DAP) approach, which leverages only weakly-labeled classification-style datasets (e.g., ImageNet) for pre-training, but is speci…
Adversarial Feature Augmentation and Normalization for Visual Recognition
Tianlong Chen, Yu Cheng, Zhe Gan +4
Recent advances in computer vision take advantage of adversarial data augmentation to ameliorate the generalization ability of classification models. Here, we present an effective…