17 citations · 26 across the 8 of their papers we have counts for
10 papers
Pixel Contrastive-Consistent Semi-Supervised Semantic Segmentation
Yuanyi Zhong, Bodi Yuan, Hong Wu +3
We present a novel semi-supervised semantic segmentation method which jointly achieves two desiderata of segmentation model regularities: the label-space consistency property betwe…
Coordinate-wise Control Variates for Deep Policy Gradients
Yuanyi Zhong, Yuan Zhou, Jian Peng
The control variates (CV) method is widely used in policy gradient estimation to reduce the variance of the gradient estimators in practice. A control variate is applied by subtrac…
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…
Shaping Deep Feature Space towards Gaussian Mixture for Visual Classification
Weitao Wan, Jiansheng Chen, Cheng Yu +3
The softmax cross-entropy loss function has been widely used to train deep models for various tasks. In this work, we propose a Gaussian mixture (GM) loss function for deep neural…
Efficient Competitive Self-Play Policy Optimization
Yuanyi Zhong, Yuan Zhou, Jian Peng
Reinforcement learning from self-play has recently reported many successes. Self-play, where the agents compete with themselves, is often used to generate training data for iterati…
Boosting Weakly Supervised Object Detection with Progressive Knowledge Transfer
Yuanyi Zhong, Jianfeng Wang, Jian Peng +1
In this paper, we propose an effective knowledge transfer framework to boost the weakly supervised object detection accuracy with the help of an external fully-annotated source dat…