Search Results for author: Yun Liang

Found 22 papers, 5 papers with code

ToCoAD: Two-Stage Contrastive Learning for Industrial Anomaly Detection

no code implementations1 Jul 2024 Yun Liang, Zhiguang Hu, JunJie Huang, Donglin Di, Anyang Su, Lei Fan

Current unsupervised anomaly detection approaches perform well on public datasets but struggle with specific anomaly types due to the domain gap between pre-trained feature extractors and target-specific domains.

Contrastive Learning Self-Supervised Learning +1

AAT: Adapting Audio Transformer for Various Acoustics Recognition Tasks

1 code implementation19 Jan 2024 Yun Liang, Hai Lin, Shaojian Qiu, Yihang Zhang

Other fine-tuning methods either struggle to address this issue or fail to achieve matching performance.

Structure-Aware Parametric Representations for Time-Resolved Light Transport

no code implementations30 Aug 2023 Diego Royo, Zesheng Huang, Yun Liang, Boyan Song, Adolfo Muñoz, Diego Gutierrez, Julio Marco

Time-resolved illumination provides rich spatio-temporal information for applications such as accurate depth sensing or hidden geometry reconstruction, becoming a useful asset for prototyping and as input for data-driven approaches.

Depth Estimation

Memory-aware Scheduling for Complex Wired Networks with Iterative Graph Optimization

no code implementations26 Aug 2023 Shuzhang Zhong, Meng Li, Yun Liang, Runsheng Wang, Ru Huang

Memory-aware network scheduling is becoming increasingly important for deep neural network (DNN) inference on resource-constrained devices.

Scheduling

On Mitigating Hard Clusters for Face Clustering

1 code implementation25 Jul 2022 Yingjie Chen, Huasong Zhong, Chong Chen, Chen Shen, Jianqiang Huang, Tao Wang, Yun Liang, Qianru Sun

Face clustering is a promising way to scale up face recognition systems using large-scale unlabeled face images.

Clustering Face Clustering +1

Causal Intervention for Subject-Deconfounded Facial Action Unit Recognition

no code implementations17 Apr 2022 Yingjie Chen, Diqi Chen, Tao Wang, Yizhou Wang, Yun Liang

Subject-invariant facial action unit (AU) recognition remains challenging for the reason that the data distribution varies among subjects.

Causal Inference Facial Action Unit Detection

Optimized Separable Convolution: Yet Another Efficient Convolution Operator

no code implementations29 Sep 2021 Tao Wei, Yonghong Tian, YaoWei Wang, Yun Liang, Chang Wen Chen

In this research, we propose a novel and principled operator called optimized separable convolution by optimal design for the internal number of groups and kernel sizes for general separable convolutions can achieve the complexity of O(C^{\frac{3}{2}}K).

Self-paced Resistance Learning against Overfitting on Noisy Labels

1 code implementation7 May 2021 Xiaoshuang Shi, Zhenhua Guo, Kang Li, Yun Liang, Xiaofeng Zhu

They might significantly deteriorate the performance of convolutional neural networks (CNNs), because CNNs are easily overfitted on corrupted labels.

Memorization

HASCO: Towards Agile HArdware and Software CO-design for Tensor Computation

1 code implementation4 May 2021 Qingcheng Xiao, Size Zheng, Bingzhe Wu, Pengcheng Xu, Xuehai Qian, Yun Liang

Second, the overall design space composed of HW/SW partitioning, hardware optimization, and software optimization is huge.

Bayesian Optimization Q-Learning

A Dual-Critic Reinforcement Learning Framework for Frame-level Bit Allocation in HEVC/H.265

no code implementations5 Apr 2021 Yung-Han Ho, Guo-Lun Jin, Yun Liang, Wen-Hsiao Peng, Xiaobo Li

This paper introduces a dual-critic reinforcement learning (RL) framework to address the problem of frame-level bit allocation in HEVC/H. 265.

reinforcement-learning Reinforcement Learning (RL)

Systolic Computing on GPUs for Productive Performance

no code implementations29 Oct 2020 Hongbo Rong, Xiaochen Hao, Yun Liang, Lidong Xu, Hong H Jiang, Pradeep Dubey

We propose a language and compiler to productively build high-performance {\it software systolic arrays} that run on GPUs.

REQ-YOLO: A Resource-Aware, Efficient Quantization Framework for Object Detection on FPGAs

no code implementations29 Sep 2019 Caiwen Ding, Shuo Wang, Ning Liu, Kaidi Xu, Yanzhi Wang, Yun Liang

To achieve real-time, highly-efficient implementations on FPGA, we present the detailed hardware implementation of block circulant matrices on CONV layers and develop an efficient processing element (PE) structure supporting the heterogeneous weight quantization, CONV dataflow and pipelining techniques, design optimization, and a template-based automatic synthesis framework to optimally exploit hardware resource.

Model Compression object-detection +2

Efficient Recurrent Neural Networks using Structured Matrices in FPGAs

no code implementations20 Mar 2018 Zhe Li, Shuo Wang, Caiwen Ding, Qinru Qiu, Yanzhi Wang, Yun Liang

Recurrent Neural Networks (RNNs) are becoming increasingly important for time series-related applications which require efficient and real-time implementations.

Model Compression Time Series +1

C-LSTM: Enabling Efficient LSTM using Structured Compression Techniques on FPGAs

no code implementations14 Mar 2018 Shuo Wang, Zhe Li, Caiwen Ding, Bo Yuan, Yanzhi Wang, Qinru Qiu, Yun Liang

The previous work proposes to use a pruning based compression technique to reduce the model size and thus speedups the inference on FPGAs.

Component-Based Distributed Framework for Coherent and Real-Time Video Dehazing

no code implementations7 Sep 2016 Meihua Wang, Jiaming Mai, Yun Liang, Tom Z. J. Fu, Zhenjie Zhang, Ruichu Cai

Traditional dehazing techniques, as a well studied topic in image processing, are now widely used to eliminate the haze effects from individual images.

Decision Making Robot Navigation

Ensemble-driven support vector clustering: From ensemble learning to automatic parameter estimation

no code implementations3 Aug 2016 Dong Huang, Chang-Dong Wang, Jian-Huang Lai, Yun Liang, Shan Bian, Yu Chen

Support vector clustering (SVC) is a versatile clustering technique that is able to identify clusters of arbitrary shapes by exploiting the kernel trick.

Clustering Ensemble Learning

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