577 citations · 1.3k across the 24 of their papers we have counts for
24 papers
ConQueR: Query Contrast Voxel-DETR for 3D Object Detection
Benjin Zhu, Zhe Wang, Shaoshuai Shi +3
Although DETR-based 3D detectors can simplify the detection pipeline and achieve direct sparse predictions, their performance still lags behind dense detectors with post-processing…
Magnetic Resonance Fingerprinting with compressed sensing and distance metric learning
Zhe Wang, Hongsheng Li, Qinwei Zhang +2
Magnetic Resonance Fingerprinting (MRF) is a novel technique that simultaneously estimates multiple tissue-related parameters, such as the longitudinal relaxation time T1, the tran…
AdaStereo: An Efficient Domain-Adaptive Stereo Matching Approach
Xiao Song, Guorun Yang, Xinge Zhu +4
Recently, records on stereo matching benchmarks are constantly broken by end-to-end disparity networks. However, the domain adaptation ability of these deep models is quite limited…
ST3D++: Denoised Self-training for Unsupervised Domain Adaptation on 3D Object Detection
Jihan Yang, Shaoshuai Shi, Zhe Wang +2
In this paper, we present a self-training method, named ST3D++, with a holistic pseudo label denoising pipeline for unsupervised domain adaptation on 3D object detection. ST3D++ ai…
Exploring Data Augmentation for Multi-Modality 3D Object Detection
Wenwei Zhang, Zhe Wang, Chen Change Loy
It is counter-intuitive that multi-modality methods based on point cloud and images perform only marginally better or sometimes worse than approaches that solely use point cloud. T…
AdaStereo: A Simple and Efficient Approach for Adaptive Stereo Matching
Xiao Song, Guorun Yang, Xinge Zhu +3
Recently, records on stereo matching benchmarks are constantly broken by end-to-end disparity networks. However, the domain adaptation ability of these deep models is quite poor. A…
SegVoxelNet: Exploring Semantic Context and Depth-aware Features for 3D Vehicle Detection from Point Cloud
Hongwei Yi, Shaoshuai Shi, Mingyu Ding +6
3D vehicle detection based on point cloud is a challenging task in real-world applications such as autonomous driving. Despite significant progress has been made, we observe two as…
Learning Depth-Guided Convolutions for Monocular 3D Object Detection
Mingyu Ding, Yuqi Huo, Hongwei Yi +4
3D object detection from a single image without LiDAR is a challenging task due to the lack of accurate depth information. Conventional 2D convolutions are unsuitable for this task…
PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection
Shaoshuai Shi, Chaoxu Guo, Li Jiang +4
We present a novel and high-performance 3D object detection framework, named PointVoxel-RCNN (PV-RCNN), for accurate 3D object detection from point clouds. Our proposed method deep…
Every Frame Counts: Joint Learning of Video Segmentation and Optical Flow
Mingyu Ding, Zhe Wang, Bolei Zhou +3
A major challenge for video semantic segmentation is the lack of labeled data. In most benchmark datasets, only one frame of a video clip is annotated, which makes most supervised…
Robust Multi-Modality Multi-Object Tracking
Wenwei Zhang, Hui Zhou, Shuyang Sun +3
Multi-sensor perception is crucial to ensure the reliability and accuracy in autonomous driving system, while multi-object tracking (MOT) improves that by tracing sequential moveme…
FocusNet: Imbalanced Large and Small Organ Segmentation with an End-to-End Deep Neural Network for Head and Neck CT Images
Yunhe Gao, Rui Huang, Ming Chen +7
In this paper, we propose an end-to-end deep neural network for solving the problem of imbalanced large and small organ segmentation in head and neck (HaN) CT images. To conduct ra…
From Points to Parts: 3D Object Detection from Point Cloud with Part-aware and Part-aggregation Network
Shaoshuai Shi, Zhe Wang, Jianping Shi +2
3D object detection from LiDAR point cloud is a challenging problem in 3D scene understanding and has many practical applications. In this paper, we extend our preliminary work Poi…
A^2-Net: Molecular Structure Estimation from Cryo-EM Density Volumes
Kui Xu, Zhe Wang, Jiangping Shi +2
Constructing of molecular structural models from Cryo-Electron Microscopy (Cryo-EM) density volumes is the critical last step of structure determination by Cryo-EM technologies. Me…
Pose Guided Human Video Generation
Ceyuan Yang, Zhe Wang, Xinge Zhu +3
Due to the emergence of Generative Adversarial Networks, video synthesis has witnessed exceptional breakthroughs. However, existing methods lack a proper representation to explicit…
Learnable Histogram: Statistical Context Features for Deep Neural Networks
Zhe Wang, Hongsheng Li, Wanli Ouyang +1
Statistical features, such as histogram, Bag-of-Words (BoW) and Fisher Vector, were commonly used with hand-crafted features in conventional classification methods, but attract les…
Video Object Segmentation with Re-identification
Xiaoxiao Li, Yuankai Qi, Zhe Wang +6
Conventional video segmentation methods often rely on temporal continuity to propagate masks. Such an assumption suffers from issues like drifting and inability to handle large dis…
Zoom-in-Net: Deep Mining Lesions for Diabetic Retinopathy Detection
Zhe Wang, Yanxin Yin, Jianping Shi +3
We propose a convolution neural network based algorithm for simultaneously diagnosing diabetic retinopathy and highlighting suspicious regions. Our contributions are two folds: 1)…
Learning Deep Representations for Scene Labeling with Semantic Context Guided Supervision
Zhe Wang, Hongsheng Li, Wanli Ouyang +1
Scene labeling is a challenging classification problem where each input image requires a pixel-level prediction map. Recently, deep-learning-based methods have shown their effectiv…
Crafting GBD-Net for Object Detection
Xingyu Zeng, Wanli Ouyang, Junjie Yan +9
The visual cues from multiple support regions of different sizes and resolutions are complementary in classifying a candidate box in object detection. Effective integration of loca…
T-CNN: Tubelets with Convolutional Neural Networks for Object Detection from Videos
Kai Kang, Hongsheng Li, Junjie Yan +8
The state-of-the-art performance for object detection has been significantly improved over the past two years. Besides the introduction of powerful deep neural networks such as Goo…
DeepID-Net: Deformable Deep Convolutional Neural Networks for Object Detection
Wanli Ouyang, Xiaogang Wang, Xingyu Zeng +8
In this paper, we propose deformable deep convolutional neural networks for generic object detection. This new deep learning object detection framework has innovations in multiple…
DeepID-Net: multi-stage and deformable deep convolutional neural networks for object detection
Wanli Ouyang, Ping Luo, Xingyu Zeng +12
In this paper, we propose multi-stage and deformable deep convolutional neural networks for object detection. This new deep learning object detection diagram has innovations in mul…
MRF denoising with compressed sensing and adaptive filtering
Zhe Wang, Qinwei Zhang, Jing Yuan +1
The recently proposed Magnetic Resonance Fingerprinting (MRF) technique can simultaneously estimate multiple parameters through dictionary matching. It has promising potentials in…