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09/19/2023
Improving CLIP Robustness with Knowledge Distillation and Self-Training
This paper examines the robustness of a multi-modal computer vision mode...
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07/18/2023
MOCA: Self-supervised Representation Learning by Predicting Masked Online Codebook Assignments
Self-supervised learning can be used for mitigating the greedy needs of ...
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01/24/2023
RangeViT: Towards Vision Transformers for 3D Semantic Segmentation in Autonomous Driving
Casting semantic segmentation of outdoor LiDAR point clouds as a 2D prob...
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12/06/2022
PØDA: Prompt-driven Zero-shot Domain Adaptation
Domain adaptation has been vastly investigated in computer vision but st...
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10/17/2022
Packed-Ensembles for Efficient Uncertainty Estimation
Deep Ensembles (DE) are a prominent approach achieving excellent perform...
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07/25/2022
Active Learning Strategies for Weakly-supervised Object Detection
Object detectors trained with weak annotations are affordable alternativ...
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07/20/2022
Latent Discriminant deterministic Uncertainty
Predictive uncertainty estimation is essential for deploying Deep Neural...
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07/18/2022
Instance-Aware Observer Network for Out-of-Distribution Object Segmentation
Recent work on Observer Network has shown promising results on Out-Of-Di...
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06/27/2022
LaRa: Latents and Rays for Multi-Camera Bird's-Eye-View Semantic Segmentation
Recent works in autonomous driving have widely adopted the bird's-eye-vi...
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03/30/2022
Image-to-Lidar Self-Supervised Distillation for Autonomous Driving Data
Segmenting or detecting objects in sparse Lidar point clouds are two imp...
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03/29/2022
UnShadowNet: Illumination Critic Guided Contrastive Learning For Shadow Removal
Shadows are frequently encountered natural phenomena that significantly ...
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03/28/2022
Solving Disjunctive Temporal Networks with Uncertainty under Restricted Time-Based Controllability using Tree Search and Graph Neural Networks
Planning under uncertainty is an area of interest in artificial intellig...
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03/23/2022
What to Hide from Your Students: Attention-Guided Masked Image Modeling
Transformers and masked language modeling are quickly being adopted and ...
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03/21/2022
Drive Segment: Unsupervised Semantic Segmentation of Urban Scenes via Cross-modal Distillation
This work investigates learning pixel-wise semantic image segmentation i...
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03/02/2022
MUAD: Multiple Uncertainties for Autonomous Driving benchmark for multiple uncertainty types and tasks
Predictive uncertainty estimation is essential for deploying Deep Neural...
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09/29/2021
Localizing Objects with Self-Supervised Transformers and no Labels
Localizing objects in image collections without supervision can help to ...
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08/03/2021
Triggering Failures: Out-Of-Distribution detection by learning from local adversarial attacks in Semantic Segmentation
In this paper, we tackle the detection of out-of-distribution (OOD) obje...
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08/02/2021
Time-based Dynamic Controllability of Disjunctive Temporal Networks with Uncertainty: A Tree Search Approach with Graph Neural Network Guidance
Scheduling in the presence of uncertainty is an area of interest in arti...
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08/02/2021
Learning-based Preference Prediction for Constrained Multi-Criteria Path-Planning
Learning-based methods are increasingly popular for search algorithms in...
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08/02/2021
Optimal Solving of Constrained Path-Planning Problems with Graph Convolutional Networks and Optimized Tree Search
Learning-based methods are growing prominence for planning purposes. How...
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08/02/2021
Constrained Shortest Path Search with Graph Convolutional Neural Networks
Planning for Autonomous Unmanned Ground Vehicles (AUGV) is still a chall...
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08/02/2021
Reliable Semantic Segmentation with Superpixel-Mix
Along with predictive performance and runtime speed, reliability is a ke...
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03/25/2021
StyleLess layer: Improving robustness for real-world driving
Deep Neural Networks (DNNs) are a critical component for self-driving ve...
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12/21/2020
Online Bag-of-Visual-Words Generation for Unsupervised Representation Learning
Learning image representations without human supervision is an important...
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12/04/2020
Encoding the latent posterior of Bayesian Neural Networks for uncertainty quantification
Bayesian neural networks (BNNs) have been long considered an ideal, yet ...
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06/23/2020
Spherical Perspective on Learning with Batch Norm
Batch Normalization (BN) is a prominent deep learning technique. In spit...
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06/01/2020
One Versus all for deep Neural Network Incertitude (OVNNI) quantification
Deep neural networks (DNNs) are powerful learning models yet their resul...
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02/27/2020
Learning Representations by Predicting Bags of Visual Words
Self-supervised representation learning targets to learn convnet-based i...
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01/07/2020
Dynamic Task Weighting Methods for Multi-task Networks in Autonomous Driving Systems
Deep multi-task networks are of particular interest for autonomous drivi...
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12/24/2019
TRADI: Tracking deep neural network weight distributions
During training, the weights of a Deep Neural Network (DNN) are optimize...
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11/07/2019
This dataset does not exist: training models from generated images
Current generative networks are increasingly proficient in generating hi...
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06/12/2019
Boosting Few-Shot Visual Learning with Self-Supervision
Few-shot learning and self-supervised learning address different facets ...
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03/12/2019
Dense Classification and Implanting for Few-Shot Learning
Training deep neural networks from few examples is a highly challenging ...
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11/27/2018
