162 citations · 354 across the 26 of their papers we have counts for
12 papers · 1 filter
PTTR: Relational 3D Point Cloud Object Tracking with Transformer
Changqing Zhou, Zhipeng Luo, Yueru Luo +5
In a point cloud sequence, 3D object tracking aims to predict the location and orientation of an object in the current search point cloud given a template point cloud. Motivated by…
GenCo: Generative Co-training for Generative Adversarial Networks with Limited Data
Kaiwen Cui, Jiaxing Huang, Zhipeng Luo +3
Training effective Generative Adversarial Networks (GANs) requires large amounts of training data, without which the trained models are usually sub-optimal with discriminator over-…
MapRE: An Effective Semantic Mapping Approach for Low-resource Relation Extraction
Manqing Dong, Chunguang Pan, Zhipeng Luo
Neural relation extraction models have shown promising results in recent years; however, the model performance drops dramatically given only a few training samples. Recent works tr…
Unsupervised Domain Adaptive 3D Detection with Multi-Level Consistency
Zhipeng Luo, Zhongang Cai, Changqing Zhou +7
Deep learning-based 3D object detection has achieved unprecedented success with the advent of large-scale autonomous driving datasets. However, drastic performance degradation rema…
VisDrone-CC2020: The Vision Meets Drone Crowd Counting Challenge Results
Dawei Du, Longyin Wen, Pengfei Zhu +52
Crowd counting on the drone platform is an interesting topic in computer vision, which brings new challenges such as small object inference, background clutter and wide viewpoint.…
Domain Consistency Regularization for Unsupervised Multi-source Domain Adaptive Classification
Zhipeng Luo, Xiaobing Zhang, Shijian Lu +1
Deep learning-based multi-source unsupervised domain adaptation (MUDA) has been actively studied in recent years. Compared with single-source unsupervised domain adaptation (SUDA),…
NTIRE 2021 Depth Guided Image Relighting Challenge
Majed El Helou, Ruofan Zhou, Sabine Susstrunk +1
Image relighting is attracting increasing interest due to its various applications. From a research perspective, image relighting can be exploited to conduct both image normalizati…
BERT-based Acronym Disambiguation with Multiple Training Strategies
Chunguang Pan, Bingyan Song, Shengguang Wang +1
Acronym disambiguation (AD) task aims to find the correct expansions of an ambiguous ancronym in a given sentence. Although it is convenient to use acronyms, sometimes they could b…
DA-DETR: Domain Adaptive Detection Transformer with Information Fusion
Jingyi Zhang, Jiaxing Huang, Zhipeng Luo +3
The recent detection transformer (DETR) simplifies the object detection pipeline by removing hand-crafted designs and hyperparameters as employed in conventional two-stage object d…
Meta-DETR: Image-Level Few-Shot Object Detection with Inter-Class Correlation Exploitation
Gongjie Zhang, Zhipeng Luo, Kaiwen Cui +1
Few-shot object detection has been extensively investigated by incorporating meta-learning into region-based detection frameworks. Despite its success, the said paradigm is constra…
Semantic Segmentation with Labeling Uncertainty and Class Imbalance
Patrik Olã Bressan, José Marcato Junior, José Augusto Correa Martins +8
Recently, methods based on Convolutional Neural Networks (CNN) achieved impressive success in semantic segmentation tasks. However, challenges such as the class imbalance and the u…
Counting and Locating High-Density Objects Using Convolutional Neural Network
Mauro dos Santos de Arruda, Lucas Prado Osco, Plabiany Rodrigo Acosta +8
This paper presents a Convolutional Neural Network (CNN) approach for counting and locating objects in high-density imagery. To the best of our knowledge, this is the first object…