Search Results for author:
Found 14 papers, 9 papers with code
Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection
To tackle the challenges, we first collect a new multi-view LiDAR-camera 3D multiple-object-tracking benchmark of highly crowded pedestrians for in-depth analysis.
Ranked #1 on
3D Pedestrian Tracking
on nuScenes validation set
A Multi-Modal Deep Learning Framework for Pan-Cancer Prognosis
By incorporating the multi-modality of patient data and joint training, UMPSNet outperforms all SOTA approaches, and moreover, it demonstrates the effectiveness and generalization ability of the proposed learning paradigm of a single model for multiple cancer types.
OpenDriver: An Open-Road Driver State Detection Dataset
Furthermore, three challenging tasks are involved in our work, namely ECG signal quality assessment, individual biometric identification based on ECG signals, and physiological signal analysis in complex driving environments.
Aircraft Ground Taxiing Deduction and Conflict Early Warning Method Based on Control Command Information
Aircraft taxiing conflict is a threat to the safety of airport operations, mainly due to the human error in control command infor-mation.
SDQ: Stochastic Differentiable Quantization with Mixed Precision
In order to deploy deep models in a computationally efficient manner, model quantization approaches have been frequently used.
Stereo Neural Vernier Caliper
We propose a new object-centric framework for learning-based stereo 3D object detection.
Joint stereo 3D object detection and implicit surface reconstruction
We present a new learning-based framework S-3D-RCNN that can recover accurate object orientation in SO(3) and simultaneously predict implicit rigid shapes from stereo RGB images.
How Do Adam and Training Strategies Help BNNs Optimization?
We show the regularization effect of second-order momentum in Adam is crucial to revitalize the weights that are dead due to the activation saturation in BNNs.
Exploring intermediate representation for monocular vehicle pose estimation
The latter question motivates us to incorporate geometry knowledge with a new loss function based on a projective invariant.
Ranked #1 on
Vehicle Pose Estimation
on KITTI Cars Hard
GSNet: Joint Vehicle Pose and Shape Reconstruction with Geometrical and Scene-aware Supervision
GSNet utilizes a unique four-way feature extraction and fusion scheme and directly regresses 6DoF poses and shapes in a single forward pass.
Ranked #1 on
Autonomous Driving
on ApolloCar3D
Cascaded deep monocular 3D human pose estimation with evolutionary training data
End-to-end deep representation learning has achieved remarkable accuracy for monocular 3D human pose estimation, yet these models may fail for unseen poses with limited and fixed training data.
Ranked #13 on
Weakly-supervised 3D Human Pose Estimation
on Human3.6M
Facial age estimation by deep residual decision making
Residual representation learning simplifies the optimization problem of learning complex functions and has been widely used by traditional convolutional neural networks.
Ranked #12 on
Age Estimation
on CACD
Visualizing the decision-making process in deep neural decision forest
Deep neural decision forest (NDF) achieved remarkable performance on various vision tasks via combining decision tree and deep representation learning.
Deep Hierarchical Machine: a Flexible Divide-and-Conquer Architecture
We propose Deep Hierarchical Machine (DHM), a model inspired from the divide-and-conquer strategy while emphasizing representation learning ability and flexibility.
