Search Results for author: Tian Ye

Found 38 papers, 18 papers with code

FACTUAL: A Novel Framework for Contrastive Learning Based Robust SAR Image Classification

no code implementations4 Apr 2024 Xu Wang, Tian Ye, Rajgopal Kannan, Viktor Prasanna

FACTUAL consists of two components: (1) Differing from existing works, a novel perturbation scheme that incorporates realistic physical adversarial attacks (such as OTSA) to build a supervised adversarial pre-training network.

Contrastive Learning Image Classification

Uncertainty-Aware SAR ATR: Defending Against Adversarial Attacks via Bayesian Neural Networks

no code implementations27 Mar 2024 Tian Ye, Rajgopal Kannan, Viktor Prasanna, Carl Busart

Adversarial attacks have demonstrated the vulnerability of Machine Learning (ML) image classifiers in Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) systems.

Adversarial Attack Decision Making +1

VersaT2I: Improving Text-to-Image Models with Versatile Reward

no code implementations27 Mar 2024 Jianshu Guo, Wenhao Chai, Jie Deng, Hsiang-Wei Huang, Tian Ye, Yichen Xu, Jiawei Zhang, Jenq-Neng Hwang, Gaoang Wang

Recent text-to-image (T2I) models have benefited from large-scale and high-quality data, demonstrating impressive performance.

Hierarchical Auto-Organizing System for Open-Ended Multi-Agent Navigation

no code implementations13 Mar 2024 Zhonghan Zhao, Kewei Chen, Dongxu Guo, Wenhao Chai, Tian Ye, Yanting Zhang, Gaoang Wang

To assess organizational behavior, we design a series of navigation tasks in the Minecraft environment, which includes searching and exploring.

Navigate

A Single Graph Convolution Is All You Need: Efficient Grayscale Image Classification

1 code implementation1 Feb 2024 Jacob Fein-Ashley, Tian Ye, Sachini Wickramasinghe, Bingyi Zhang, Rajgopal Kannan, Viktor Prasanna

Our experimental results on benchmark grayscale image datasets demonstrate the effectiveness of the proposed model, achieving vastly lower latency (up to 16$\times$ less) and competitive or leading performance compared to other state-of-the-art image classification models on various domain-specific grayscale image classification datasets.

Image Classification Medical Image Classification

SegMamba: Long-range Sequential Modeling Mamba For 3D Medical Image Segmentation

1 code implementation24 Jan 2024 Zhaohu Xing, Tian Ye, Yijun Yang, Guang Liu, Lei Zhu

Our SegMamba, in contrast to Transformer-based methods, excels in whole volume feature modeling from a state space model standpoint, maintaining superior processing speed, even with volume features at a resolution of {$64\times 64\times 64$}.

Image Segmentation Medical Image Segmentation +1

VQCNIR: Clearer Night Image Restoration with Vector-Quantized Codebook

1 code implementation14 Dec 2023 Wenbin Zou, Hongxia Gao, Tian Ye, Liang Chen, Weipeng Yang, Shasha Huang, Hongsheng Chen, Sixiang Chen

In this paper, we propose Clearer Night Image Restoration with Vector-Quantized Codebook (VQCNIR) to achieve remarkable and consistent restoration outcomes on real-world and synthetic benchmarks.

Image Restoration

Benchmarking Deep Learning Classifiers for SAR Automatic Target Recognition

no code implementations12 Dec 2023 Jacob Fein-Ashley, Tian Ye, Rajgopal Kannan, Viktor Prasanna, Carl Busart

Synthetic Aperture Radar SAR Automatic Target Recognition ATR is a key technique of remote-sensing image recognition which can be supported by deep neural networks The existing works of SAR ATR mostly focus on improving the accuracy of the target recognition while ignoring the systems performance in terms of speed and storage which is critical to real-world applications of SAR ATR For decision-makers aiming to identify a proper deep learning model to deploy in a SAR ATR system it is important to understand the performance of different candidate deep learning models and determine the best model accordingly This paper comprehensively benchmarks several advanced deep learning models for SAR ATR with multiple distinct SAR imagery datasets Specifically we train and test five SAR image classifiers based on Residual Neural Networks ResNet18 ResNet34 ResNet50 Graph Neural Network GNN and Vision Transformer for Small-Sized Datasets (SS-ViT) We select three datasets MSTAR GBSAR and SynthWakeSAR that offer heterogeneity We evaluate and compare the five classifiers concerning their classification accuracy runtime performance in terms of inference throughput and analytical performance in terms of number of parameters number of layers model size and number of operations Experimental results show that the GNN classifier outperforms with respect to throughput and latency However it is also shown that no clear model winner emerges from all of our chosen metrics and a one model rules all case is doubtful in the domain of SAR ATR

Benchmarking

Realistic Scatterer Based Adversarial Attacks on SAR Image Classifiers

no code implementations5 Dec 2023 Tian Ye, Rajgopal Kannan, Viktor Prasanna, Carl Busart, Lance Kaplan

Instead, adversarial attacks should be able to be implemented by physical actions, for example, placing additional false objects as scatterers around the on-ground target to perturb the SAR image and fool the SAR ATR.

Adversarial Attack

See and Think: Embodied Agent in Virtual Environment

no code implementations26 Nov 2023 Zhonghan Zhao, Wenhao Chai, Xuan Wang, Li Boyi, Shengyu Hao, Shidong Cao, Tian Ye, Jenq-Neng Hwang, Gaoang Wang

Vision perception involves the interpretation of visual information in the environment, which is then integrated into the LLMs component with agent state and task instruction.

Question Answering Retrieval

Reti-Diff: Illumination Degradation Image Restoration with Retinex-based Latent Diffusion Model

1 code implementation20 Nov 2023 Chunming He, Chengyu Fang, Yulun Zhang, Tian Ye, Kai Li, Longxiang Tang, Zhenhua Guo, Xiu Li, Sina Farsiu

These priors are subsequently utilized by RGformer to guide the decomposition of image features into their respective reflectance and illumination components.

Image Restoration

Integrating View Conditions for Image Synthesis

1 code implementation24 Oct 2023 Jinbin Bai, Zhen Dong, Aosong Feng, Xiao Zhang, Tian Ye, Kaicheng Zhou, Mike Zheng Shou

In the field of image processing, applying intricate semantic modifications within existing images remains an enduring challenge.

Image Generation Object

Sparse Sampling Transformer with Uncertainty-Driven Ranking for Unified Removal of Raindrops and Rain Streaks

1 code implementation ICCV 2023 Sixiang Chen, Tian Ye, Jinbin Bai, ErKang Chen, Jun Shi, Lei Zhu

In the real world, image degradations caused by rain often exhibit a combination of rain streaks and raindrops, thereby increasing the challenges of recovering the underlying clean image.

Rain Removal

NightHazeFormer: Single Nighttime Haze Removal Using Prior Query Transformer

1 code implementation16 May 2023 Yun Liu, Zhongsheng Yan, Sixiang Chen, Tian Ye, Wenqi Ren, ErKang Chen

Extensive experiments on several synthetic and real-world datasets demonstrate the superiority of our NightHazeFormer over state-of-the-art nighttime haze removal methods in terms of both visually and quantitatively.

Image Dehazing

Five A$^{+}$ Network: You Only Need 9K Parameters for Underwater Image Enhancement

1 code implementation15 May 2023 Jingxia Jiang, Tian Ye, Jinbin Bai, Sixiang Chen, Wenhao Chai, Shi Jun, Yun Liu, ErKang Chen

In this work, we propose the Five A$^{+}$ Network (FA$^{+}$Net), a highly efficient and lightweight real-time underwater image enhancement network with only $\sim$ 9k parameters and $\sim$ 0. 01s processing time.

Computational Efficiency Image Enhancement

RSFDM-Net: Real-time Spatial and Frequency Domains Modulation Network for Underwater Image Enhancement

no code implementations23 Feb 2023 Jingxia Jiang, Jinbin Bai, Yun Liu, Junjie Yin, Sixiang Chen, Tian Ye, ErKang Chen

Underwater images typically experience mixed degradations of brightness and structure caused by the absorption and scattering of light by suspended particles.

Image Enhancement

Adverse Weather Removal with Codebook Priors

no code implementations ICCV 2023 Tian Ye, Sixiang Chen, Jinbin Bai, Jun Shi, Chenghao Xue, Jingxia Jiang, Junjie Yin, ErKang Chen, Yun Liu

Inspired by recent advancements in codebook and vector quantization (VQ) techniques, we present a novel Adverse Weather Removal network with Codebook Priors (AWRCP) to address the problem of unified adverse weather removal.

Quantization

Dual-former: Hybrid Self-attention Transformer for Efficient Image Restoration

no code implementations3 Oct 2022 Sixiang Chen, Tian Ye, Yun Liu, ErKang Chen

Recently, image restoration transformers have achieved comparable performance with previous state-of-the-art CNNs.

Image Dehazing Image Restoration +2

SnowFormer: Context Interaction Transformer with Scale-awareness for Single Image Desnowing

1 code implementation20 Aug 2022 Sixiang Chen, Tian Ye, Yun Liu, ErKang Chen

Due to various and complicated snow degradations, single image desnowing is a challenging image restoration task.

Single Image Desnowing

Towards Real-time High-Definition Image Snow Removal: Efficient Pyramid Network with Asymmetrical Encoder-decoder Architecture

no code implementations12 Jul 2022 Tian Ye, Sixiang Chen, Yun Liu, Yi Ye, ErKang Chen

In winter scenes, the degradation of images taken under snow can be pretty complex, where the spatial distribution of snowy degradation is varied from image to image.

Snow Removal

Prior-Guided One-shot Neural Architecture Search

1 code implementation27 Jun 2022 Peijie Dong, Xin Niu, Lujun Li, Linzhen Xie, Wenbin Zou, Tian Ye, Zimian Wei, Hengyue Pan

In this paper, we present Prior-Guided One-shot NAS (PGONAS) to strengthen the ranking correlation of supernets.

Neural Architecture Search

NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results

2 code implementations11 May 2022 Yawei Li, Kai Zhang, Radu Timofte, Luc van Gool, Fangyuan Kong, Mingxi Li, Songwei Liu, Zongcai Du, Ding Liu, Chenhui Zhou, Jingyi Chen, Qingrui Han, Zheyuan Li, Yingqi Liu, Xiangyu Chen, Haoming Cai, Yu Qiao, Chao Dong, Long Sun, Jinshan Pan, Yi Zhu, Zhikai Zong, Xiaoxiao Liu, Zheng Hui, Tao Yang, Peiran Ren, Xuansong Xie, Xian-Sheng Hua, Yanbo Wang, Xiaozhong Ji, Chuming Lin, Donghao Luo, Ying Tai, Chengjie Wang, Zhizhong Zhang, Yuan Xie, Shen Cheng, Ziwei Luo, Lei Yu, Zhihong Wen, Qi Wu1, Youwei Li, Haoqiang Fan, Jian Sun, Shuaicheng Liu, Yuanfei Huang, Meiguang Jin, Hua Huang, Jing Liu, Xinjian Zhang, Yan Wang, Lingshun Long, Gen Li, Yuanfan Zhang, Zuowei Cao, Lei Sun, Panaetov Alexander, Yucong Wang, Minjie Cai, Li Wang, Lu Tian, Zheyuan Wang, Hongbing Ma, Jie Liu, Chao Chen, Yidong Cai, Jie Tang, Gangshan Wu, Weiran Wang, Shirui Huang, Honglei Lu, Huan Liu, Keyan Wang, Jun Chen, Shi Chen, Yuchun Miao, Zimo Huang, Lefei Zhang, Mustafa Ayazoğlu, Wei Xiong, Chengyi Xiong, Fei Wang, Hao Li, Ruimian Wen, Zhijing Yang, Wenbin Zou, Weixin Zheng, Tian Ye, Yuncheng Zhang, Xiangzhen Kong, Aditya Arora, Syed Waqas Zamir, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Dandan Gaoand Dengwen Zhouand Qian Ning, Jingzhu Tang, Han Huang, YuFei Wang, Zhangheng Peng, Haobo Li, Wenxue Guan, Shenghua Gong, Xin Li, Jun Liu, Wanjun Wang, Dengwen Zhou, Kun Zeng, Hanjiang Lin, Xinyu Chen, Jinsheng Fang

The aim was to design a network for single image super-resolution that achieved improvement of efficiency measured according to several metrics including runtime, parameters, FLOPs, activations, and memory consumption while at least maintaining the PSNR of 29. 00dB on DIV2K validation set.

Image Super-Resolution

Towards Efficient Single Image Dehazing and Desnowing

no code implementations19 Apr 2022 Tian Ye, Sixiang Chen, Yun Liu, ErKang Chen, Yuche Li

A single expert network efficiently addresses specific degradation in nasty winter scenes relying on the compact architecture and three novel components.

Image Dehazing Image Restoration +1

Self-Calibrated Efficient Transformer for Lightweight Super-Resolution

1 code implementation19 Apr 2022 Wenbin Zou, Tian Ye, Weixin Zheng, Yunchen Zhang, Liang Chen, Yi Wu

Recently, deep learning has been successfully applied to the single-image super-resolution (SISR) with remarkable performance.

Image Super-Resolution

Underwater Light Field Retention : Neural Rendering for Underwater Imaging

1 code implementation21 Mar 2022 Tian Ye, Sixiang Chen, Yun Liu, Yi Ye, ErKang Chen, Yuche Li

To this end, we propose a neural rendering method for underwater imaging, dubbed UWNR (Underwater Neural Rendering).

Image Enhancement Image Generation +1

Mutual Learning for Domain Adaptation: Self-distillation Image Dehazing Network with Sample-cycle

no code implementations17 Mar 2022 Tian Ye, Yun Liu, Yunchen Zhang, Sixiang Chen, ErKang Chen

Specifically, we first devise two siamese networks: a teacher network in the synthetic domain and a student network in the real domain, and then optimize them in a mutual learning manner by leveraging EMA and joint loss.

Domain Adaptation Image Dehazing

Perceiving and Modeling Density is All You Need for Image Dehazing

1 code implementation18 Nov 2021 Tian Ye, Mingchao Jiang, Yunchen Zhang, Liang Chen, ErKang Chen, Pen Chen, Zhiyong Lu

However, due to the paradox caused by the variation of real captured haze and the fixed degradation parameters of the current networks, the generalization ability of recent dehazing methods on real-world hazy images is not ideal. To address the problem of modeling real-world haze degradation, we propose to solve this problem by perceiving and modeling density for uneven haze distribution.

Image Dehazing Single Image Dehazing

Efficient Re-parameterization Residual Attention Network For Nonhomogeneous Image Dehazing

1 code implementation12 Sep 2021 Tian Ye, ErKang Chen, XinRui Huang, Peng Chen

This paper proposes an end-to-end Efficient Re-parameterizationResidual Attention Network(ERRA-Net) to directly restore the nonhomogeneous hazy image.

Image Dehazing Nonhomogeneous Image Dehazing

Global Convergence of Gradient Descent for Asymmetric Low-Rank Matrix Factorization

no code implementations NeurIPS 2021 Tian Ye, Simon S. Du

We study the asymmetric low-rank factorization problem: \[\min_{\mathbf{U} \in \mathbb{R}^{m \times d}, \mathbf{V} \in \mathbb{R}^{n \times d}} \frac{1}{2}\|\mathbf{U}\mathbf{V}^\top -\mathbf{\Sigma}\|_F^2\] where $\mathbf{\Sigma}$ is a given matrix of size $m \times n$ and rank $d$.

Matrix Completion

Aligning Videos in Space and Time

no code implementations ECCV 2020 Senthil Purushwalkam, Tian Ye, Saurabh Gupta, Abhinav Gupta

During training, given a pair of videos, we compute cycles that connect patches in a given frame in the first video by matching through frames in the second video.

DEED: A General Quantization Scheme for Communication Efficiency in Bits

no code implementations19 Jun 2020 Tian Ye, Peijun Xiao, Ruoyu Sun

In the infrequent communication setting, DEED combined with Federated averaging requires a smaller total number of bits than Federated Averaging.

Distributed Optimization Federated Learning +1

Graph Star Net for Generalized Multi-Task Learning

1 code implementation21 Jun 2019 Lu Haonan, Seth H. Huang, Tian Ye, Guo Xiuyan

In this work, we present graph star net (GraphStar), a novel and unified graph neural net architecture which utilizes message-passing relay and attention mechanism for multiple prediction tasks - node classification, graph classification and link prediction.

General Classification Graph Classification +6

Interpretable Intuitive Physics Model

no code implementations ECCV 2018 Tian Ye, Xiaolong Wang, James Davidson, Abhinav Gupta

In order to demonstrate that our system models these underlying physical properties, we train our model on collisions of different shapes (cube, cone, cylinder, spheres etc.)

Friction

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