Search Results for author: Zhun Sun

Found 19 papers, 6 papers with code

Evolutionary Topology Search for Tensor Network Decomposition

no code implementations ICML 2020 Chao Li, Zhun Sun

Tensor network (TN) decomposition is a promising framework to represent extremely high-dimensional problems with few parameters.

Evolutionary Algorithms

What Can Simple Arithmetic Operations Do for Temporal Modeling?

1 code implementation ICCV 2023 Wenhao Wu, Yuxin Song, Zhun Sun, Jingdong Wang, Chang Xu, Wanli Ouyang

We conduct comprehensive ablation studies on the instantiation of ATMs and demonstrate that this module provides powerful temporal modeling capability at a low computational cost.

Action Classification Action Recognition +1

Rethinking Prototypical Contrastive Learning through Alignment, Uniformity and Correlation

no code implementations18 Oct 2022 Shentong Mo, Zhun Sun, Chao Li

Particularly, in the classification down-stream tasks with linear probes, our proposed method outperforms the state-of-the-art instance-wise and prototypical contrastive learning methods on the ImageNet-100 dataset by 2. 96% and the ImageNet-1K dataset by 2. 46% under the same settings of batch size and epochs.

Contrastive Learning Self-Supervised Learning

Design of the topology for contrastive visual-textual alignment

no code implementations5 Sep 2022 Zhun Sun

Pre-training weakly related image-text pairs in the contrastive style shows great power in learning semantic aligning cross-modal models.

Image-to-Text Retrieval Retrieval +1

Siamese Prototypical Contrastive Learning

no code implementations18 Aug 2022 Shentong Mo, Zhun Sun, Chao Li

One of the drawbacks of CSL is that the loss term requires a large number of negative samples to provide better mutual information bound ideally.

Contrastive Learning Self-Supervised Learning

Piecing and Chipping: An effective solution for the information-erasing view generation in Self-supervised Learning

no code implementations29 Sep 2021 Jingwei Liu, Yi Gu, Shentong Mo, Zhun Sun, Shumin Han, Jiafeng Guo, Xueqi Cheng

In self-supervised learning frameworks, deep networks are optimized to align different views of an instance that contains the similar visual semantic information.

Data Augmentation Self-Supervised Learning

Representation Disentanglement in Generative Models with Contrastive Learning

no code implementations29 Sep 2021 Shentong Mo, Zhun Sun, Shumin Han

Recent works apply the contrastive learning on the discriminator of the Generative Adversarial Networks, and there exists little work on exploring if contrastive learning can be applied on encoders to learn disentangled representations.

Contrastive Learning Disentanglement +1

On the Memory Mechanism of Tensor-Power Recurrent Models

1 code implementation2 Mar 2021 Hejia Qiu, Chao Li, Ying Weng, Zhun Sun, Xingyu He, Qibin Zhao

Tensor-power (TP) recurrent model is a family of non-linear dynamical systems, of which the recurrence relation consists of a p-fold (a. k. a., degree-p) tensor product.

Low-Rank Embedding of Kernels in Convolutional Neural Networks under Random Shuffling

no code implementations31 Oct 2018 Chao Li, Zhun Sun, Jinshi Yu, Ming Hou, Qibin Zhao

We demonstrate this by compressing the convolutional layers via randomly-shuffled tensor decomposition (RsTD) for a standard classification task using CIFAR-10.

General Classification Tensor Decomposition

Feature Quantization for Defending Against Distortion of Images

no code implementations CVPR 2018 Zhun Sun, Mete Ozay, Yan Zhang, Xing Liu, Takayuki Okatani

In this work, we address the problem of improving robustness of convolutional neural networks (CNNs) to image distortion.


Beyond Unfolding: Exact Recovery of Latent Convex Tensor Decomposition under Reshuffling

no code implementations22 May 2018 Chao Li, Mohammad Emtiyaz Khan, Zhun Sun, Gang Niu, Bo Han, Shengli Xie, Qibin Zhao

Exact recovery of tensor decomposition (TD) methods is a desirable property in both unsupervised learning and scientific data analysis.

Image Steganography Tensor Decomposition

HyperNetworks with statistical filtering for defending adversarial examples

no code implementations6 Nov 2017 Zhun Sun, Mete Ozay, Takayuki Okatani

This problem was addressed by employing several defense methods for detection and rejection of particular types of attacks.

General Classification Image Classification

Improving Robustness of Feature Representations to Image Deformations using Powered Convolution in CNNs

no code implementations25 Jul 2017 Zhun Sun, Mete Ozay, Takayuki Okatani

In this work, we address the problem of improvement of robustness of feature representations learned using convolutional neural networks (CNNs) to image deformation.

object-detection Object Detection +1

Linear Discriminant Generative Adversarial Networks

no code implementations25 Jul 2017 Zhun Sun, Mete Ozay, Takayuki Okatani

We develop a novel method for training of GANs for unsupervised and class conditional generation of images, called Linear Discriminant GAN (LD-GAN).

Information Potential Auto-Encoders

no code implementations14 Jun 2017 Yan Zhang, Mete Ozay, Zhun Sun, Takayuki Okatani

In order to estimate the entropy of the encoding variables and the mutual information, we propose a non-parametric method.

Representation Learning

Design of Kernels in Convolutional Neural Networks for Image Classification

1 code implementation30 Nov 2015 Zhun Sun, Mete Ozay, Takayuki Okatani

Despite the effectiveness of Convolutional Neural Networks (CNNs) for image classification, our understanding of the relationship between shape of convolution kernels and learned representations is limited.

Classification General Classification +1

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