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Network Automatic Pruning: Start NAP and Take a Nap
Network pruning can significantly reduce the computation and memory foot...
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Cost-Efficient Online Hyperparameter Optimization
Recent work on hyperparameters optimization (HPO) has shown the possibil...
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Self-Supervised Representation Learning from Flow Equivariance
Self-supervised representation learning is able to learn semantically me...
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Safety-Oriented Pedestrian Motion and Scene Occupancy Forecasting
In this paper, we address the important problem in self-driving of forec...
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Weakly-supervised 3D Shape Completion in the Wild
3D shape completion for real data is important but challenging, since pa...
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LoCo: Local Contrastive Representation Learning
Deep neural nets typically perform end-to-end backpropagation to learn t...
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LevelSet R-CNN: A Deep Variational Method for Instance Segmentation
Obtaining precise instance segmentation masks is of high importance in m...
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PolyTransform: Deep Polygon Transformer for Instance Segmentation
In this paper, we propose PolyTransform, a novel instance segmentation a...
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Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction
Self-driving vehicles plan around both static and dynamic objects, apply...
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Learning to Remember from a Multi-Task Teacher
Recent studies on catastrophic forgetting during sequential learning typ...
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DMM-Net: Differentiable Mask-Matching Network for Video Object Segmentation
In this paper, we propose the differentiable mask-matching network (DMM-...
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Deformable Filter Convolution for Point Cloud Reasoning
Point clouds are the native output of many real-world 3D sensors. To bor...
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Deep Rigid Instance Scene Flow
In this paper we tackle the problem of scene flow estimation in the cont...
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UPSNet: A Unified Panoptic Segmentation Network
In this paper, we propose a unified panoptic segmentation network (UPSNe...
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Inference in Probabilistic Graphical Models by Graph Neural Networks
A useful computation when acting in a complex environment is to infer th...
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Reviving and Improving Recurrent Back-Propagation
In this paper, we revisit the recurrent back-propagation (RBP) algorithm...
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Deformable Convolutional Networks
Convolutional neural networks (CNNs) are inherently limited to model geo...
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Deep Feature Flow for Video Recognition
Deep convolutional neutral networks have achieved great success on image...
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