Search Results for author: Duo Li

Found 19 papers, 11 papers with code

Accelerating the Evolution of Personalized Automated Lane Change through Lesson Learning

no code implementations13 May 2024 Jia Hu, Mingyue Lei, Duo Li, Zhenning Li, Jaehyun, So, Haoran Wang

Guided by the objective of optimizing rewards within the constraints of the driving zone, this approach employs model predictive control for trajectory planning.

Computational Efficiency Model Predictive Control +1

Few-Shot Class-Incremental Learning with Prior Knowledge

1 code implementation2 Feb 2024 Wenhao Jiang, Duo Li, Menghan Hu, Guangtao Zhai, Xiaokang Yang, Xiao-Ping Zhang

To tackle the issues of catastrophic forgetting and overfitting in few-shot class-incremental learning (FSCIL), previous work has primarily concentrated on preserving the memory of old knowledge during the incremental phase.

Few-Shot Class-Incremental Learning Incremental Learning

Uncertainty-aware Sampling for Long-tailed Semi-supervised Learning

1 code implementation9 Jan 2024 Kuo Yang, Duo Li, Menghan Hu, Guangtao Zhai, Xiaokang Yang, Xiao-Ping Zhang

This approach allows the model to perceive the uncertainty of pseudo-labels at different training stages, thereby adaptively adjusting the selection thresholds for different classes.

Pseudo Label

E2-AEN: End-to-End Incremental Learning with Adaptively Expandable Network

no code implementations14 Jul 2022 Guimei Cao, Zhanzhan Cheng, Yunlu Xu, Duo Li, ShiLiang Pu, Yi Niu, Fei Wu

In this paper, we propose an end-to-end trainable adaptively expandable network named E2-AEN, which dynamically generates lightweight structures for new tasks without any accuracy drop in previous tasks.

Incremental Learning

m-RevNet: Deep Reversible Neural Networks with Momentum

no code implementations12 Aug 2021 Duo Li, Shang-Hua Gao

In recent years, the connections between deep residual networks and first-order Ordinary Differential Equations (ODEs) have been disclosed.

Image Classification Semantic Segmentation

Unifying Nonlocal Blocks for Neural Networks

1 code implementation ICCV 2021 Lei Zhu, Qi She, Duo Li, Yanye Lu, Xuejing Kang, Jie Hu, Changhu Wang

The nonlocal-based blocks are designed for capturing long-range spatial-temporal dependencies in computer vision tasks.

Action Recognition Image Classification +2

Representative Batch Normalization With Feature Calibration

no code implementations CVPR 2021 Shang-Hua Gao, Qi Han, Duo Li, Ming-Ming Cheng, Pai Peng

We propose to add a simple yet effective feature calibration scheme into the centering and scaling operations of BatchNorm, enhancing the instance-specific representations with the negligible computational cost.

Potential Convolution: Embedding Point Clouds into Potential Fields

no code implementations5 Apr 2021 Dengsheng Chen, Haowen Deng, Jun Li, Duo Li, Yao Duan, Kai Xu

In this work, rather than defining a continuous or discrete kernel, we directly embed convolutional kernels into the learnable potential fields, giving rise to potential convolution.

3D Shape Classification Scene Segmentation

Learning the Superpixel in a Non-iterative and Lifelong Manner

1 code implementation CVPR 2021 Lei Zhu, Qi She, Bin Zhang, Yanye Lu, Zhilin Lu, Duo Li, Jie Hu

Superpixel is generated by automatically clustering pixels in an image into hundreds of compact partitions, which is widely used to perceive the object contours for its excellent contour adherence.

Clustering

PointFlow: Flowing Semantics Through Points for Aerial Image Segmentation

1 code implementation CVPR 2021 Xiangtai Li, Hao He, Xia Li, Duo Li, Guangliang Cheng, Jianping Shi, Lubin Weng, Yunhai Tong, Zhouchen Lin

Experimental results on three different aerial segmentation datasets suggest that the proposed method is more effective and efficient than state-of-the-art general semantic segmentation methods.

Image Segmentation Segmentation +1

Rethinking Pseudo-labeled Sample Mining for Semi-Supervised Object Detection

no code implementations1 Jan 2021 Duo Li, Sanli Tang, Zhanzhan Cheng, ShiLiang Pu, Yi Niu, Wenming Tan, Fei Wu, Xiaokang Yang

However, the impact of the pseudo-labeled samples' quality as well as the mining strategies for high quality training sample have rarely been studied in SSL.

object-detection Object Detection +1

Resolution Switchable Networks for Runtime Efficient Image Recognition

1 code implementation ECCV 2020 Yikai Wang, Fuchun Sun, Duo Li, Anbang Yao

We propose a general method to train a single convolutional neural network which is capable of switching image resolutions at inference.

Knowledge Distillation Quantization

Learning to Learn Parameterized Classification Networks for Scalable Input Images

1 code implementation ECCV 2020 Duo Li, Anbang Yao, Qifeng Chen

To achieve efficient and flexible image classification at runtime, we employ meta learners to generate convolutional weights of main networks for various input scales and maintain privatized Batch Normalization layers per scale.

Classification General Classification +2

PSConv: Squeezing Feature Pyramid into One Compact Poly-Scale Convolutional Layer

1 code implementation ECCV 2020 Duo Li, Anbang Yao, Qifeng Chen

Despite their strong modeling capacities, Convolutional Neural Networks (CNNs) are often scale-sensitive.

Representation Learning

Deep Reinforced Attention Learning for Quality-Aware Visual Recognition

no code implementations ECCV 2020 Duo Li, Qifeng Chen

In this paper, we build upon the weakly-supervised generation mechanism of intermediate attention maps in any convolutional neural networks and disclose the effectiveness of attention modules more straightforwardly to fully exploit their potential.

Dynamic Hierarchical Mimicking Towards Consistent Optimization Objectives

1 code implementation CVPR 2020 Duo Li, Qifeng Chen

While the depth of modern Convolutional Neural Networks (CNNs) surpasses that of the pioneering networks with a significant margin, the traditional way of appending supervision only over the final classifier and progressively propagating gradient flow upstream remains the training mainstay.

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions

1 code implementation ICCV 2019 Duo Li, Aojun Zhou, Anbang Yao

MobileNets, a class of top-performing convolutional neural network architectures in terms of accuracy and efficiency trade-off, are increasingly used in many resourceaware vision applications.

object-detection Object Detection +2

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