Search Results for author: Zhennan Wang

Found 7 papers, 3 papers with code

Fuzzy Positive Learning for Semi-supervised Semantic Segmentation

no code implementations16 Oct 2022 Pengchong Qiao, Zhidan Wei, Yu Wang, Zhennan Wang, Guoli Song, Fan Xu, Xiangyang Ji, Chang Liu, Jie Chen

Semi-supervised learning (SSL) essentially pursues class boundary exploration with less dependence on human annotations.

Semi-Supervised Semantic Segmentation

ACSeg: Adaptive Conceptualization for Unsupervised Semantic Segmentation

no code implementations12 Oct 2022 Kehan Li, Zhennan Wang, Zesen Cheng, Runyi Yu, Yian Zhao, Guoli Song, Chang Liu, Li Yuan, Jie Chen

Recently, self-supervised large-scale visual pre-training models have shown great promise in representing pixel-level semantic relationships, significantly promoting the development of unsupervised dense prediction tasks, e. g., unsupervised semantic segmentation (USS).

Image Segmentation Unsupervised Semantic Segmentation

Locality Guidance for Improving Vision Transformers on Tiny Datasets

1 code implementation20 Jul 2022 Kehan Li, Runyi Yu, Zhennan Wang, Li Yuan, Guoli Song, Jie Chen

Therefore, our locality guidance approach is very simple and efficient, and can serve as a basic performance enhancement method for VTs on tiny datasets.

$L_2$BN: Enhancing Batch Normalization by Equalizing the $L_2$ Norms of Features

no code implementations6 Jul 2022 Zhennan Wang, Kehan Li, Runyi Yu, Yian Zhao, Pengchong Qiao, Fan Xu, Guoli Song, Jie Chen

In this paper, we show that the difference in $l_2$ norms of sample features can hinder batch normalization from obtaining more distinguished inter-class features and more compact intra-class features.

Acoustic Scene Classification Image Classification +1

DPR-CAE: Capsule Autoencoder with Dynamic Part Representation for Image Parsing

no code implementations30 Apr 2021 Canqun Xiang, Zhennan Wang, Wenbin Zou, Chen Xu

Parsing an image into a hierarchy of objects, parts, and relations is important and also challenging in many computer vision tasks.


MMA Regularization: Decorrelating Weights of Neural Networks by Maximizing the Minimal Angles

1 code implementation NeurIPS 2020 Zhennan Wang, Canqun Xiang, Wenbin Zou, Chen Xu

Extensive experiments demonstrate that MMA regularization is able to enhance the generalization ability of various modern models and achieves considerable performance improvements on CIFAR100 and TinyImageNet datasets.

Face Verification

PR Product: A Substitute for Inner Product in Neural Networks

1 code implementation ICCV 2019 Zhennan Wang, Wenbin Zou, Chen Xu

In this paper, we analyze the inner product of weight vector w and data vector x in neural networks from the perspective of vector orthogonal decomposition and prove that the direction gradient of w decreases with the angle between them close to 0 or {\pi}.

General Classification Image Captioning +1

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