On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,982 papers · 148 categories

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10 results for “nuScenes”

nuScenes: A multimodal dataset for autonomous drivingcs.LG

nuScenes dataset includes multimodal sensor data for autonomous vehicle training.

problem Training robust detection and tracking methods for autonomous vehicles.

method Presented the first multimodal dataset with 6 cameras, 5 radars, and 1 lidar, 360-degree field of view.

result 7x more annotations and 100x more images than KITTI dataset.

autonomous driving multimodal dataset nuScenes object detection tracking

2019-03-26abs ↗pdf ↗

Doubly Robust Self-Trainingcs.LG

Doubly robust self-training improves semi-supervised learning by balancing labeled and pseudo-labeled data.

problem Improving semi-supervised learning performance with limited labeled data.

method Introduces doubly robust self-training, a method that combines labeled and pseudo-labeled data to balance between labeled-only and pseudo-labeled-only training.

result Demonstrates superior performance of doubly robust self-training on ImageNet and nuScenes datasets.

semi-supervised learning self-training pseudo-labels doubly robust image classification

2023-06-01abs ↗pdf ↗

Map-Adaptive Goal-Based Trajectory Predictioncs.LG

New method predicts vehicle trajectories using map lane centers.

problem Accurate long-term vehicle trajectory prediction.

method Uses map lane centers to generate goal paths and predict trajectories.

result Model outperforms state-of-the-art approaches for 6-second horizon predictions.

trajectory prediction vehicle behavior map-based long-term goal-based

2020-09-09abs ↗pdf ↗

PointPainting: Sequential Fusion for 3D Object Detectioncs.CV

PointPainting fuses lidar and image data for better 3D object detection.

problem Lidar-only methods outperform fusion methods on 3D object detection benchmarks.

method Sequential fusion by projecting lidar points into image segmentation output and appending class scores.

result Significant improvements on state-of-the-art 3D object detection methods on KITTI and nuScenes datasets.

3D object detection lidar fusion sequential semantic segmentation

2019-11-22abs ↗pdf ↗

Guided Conditional Diffusion for Controllable Traffic Simulationcs.RO

Develops a new model for controllable and realistic traffic simulation.

problem Lack of models that offer both controllability and realism in traffic simulation.

method Guided Conditional Diffusion (CTG) model using diffusion modeling and differentiable logic.

result Improves controllability-realism tradeoff over strong baselines.

traffic simulation conditional diffusion diffusion modeling autonomous vehicles controllability

2022-10-31abs ↗pdf ↗

VTrackIt: A Synthetic Self-Driving Dataset with Infrastructure and Pooled Vehicle Informationcs.CV

VTrackIt creates a synthetic dataset with infrastructure and vehicle info for AVs.

problem Lack of infrastructure and pooled vehicle info in existing AV datasets.

method Developed VTrackIt, a synthetic dataset with intelligent infrastructure and pooled vehicle info, and introduced InfraGAN for trajectory predictions.

result VTrackIt reduces high-risk edge cases in AV trajectory predictions.

AVs Synthetic Dataset Infrastructure Pooled Vehicle Info Trajectory Prediction

2022-07-15abs ↗pdf ↗

Random-Set Graph Neural Networkscs.AI

New framework models epistemic uncertainty in GNNs using random sets.

problem Uncertainty in graph neural network predictions.

method Introduces a belief function (random set) approach to model epistemic uncertainty in GNNs.

result Demonstrates superior uncertainty quantification on various graph datasets.

Graph Neural Networks Uncertainty Quantification Random Sets Epistemic Uncertainty Belief Function

2026-05-12abs ↗pdf ↗

Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts?cs.LG

Paper proposes methods to help autonomous vehicles adapt to unexpected driving scenarios.

problem Autonomous vehicles struggle with unexpected driving conditions.

method Robust imitative planning (RIP) and adaptive robust imitative planning (AdaRIP) methods to detect and adapt to distribution shifts.

result Methods outperform current state-of-the-art approaches in nuScenes prediction challenge.

autonomous vehicles distribution shifts epistemic uncertainty imitative planning novel scenes

2020-06-26abs ↗pdf ↗

Bayesian Multiobject Tracking With Neural-Enhanced Motion and Measurement Modelscs.LG

Hybrid Bayesian MOT uses neural networks to improve model aspects, achieving state-of-the-art performance.

problem Improving multiobject tracking performance across various scenarios.

method Hybrid approach combining neural network enhancements with Bayesian estimation and belief propagation.

result State-of-the-art performance in autonomous driving dataset evaluation.

Bayesian MOT Neural networks Multiobject tracking Autonomous driving Data-driven

2025-06-22abs ↗pdf ↗

Collaborative Uncertainty Benefits Multi-Agent Multi-Modal Trajectory Forecastingcs.CV

This work tackles uncertainty in multi-agent multi-modal trajectory forecasting.

problem Measuring and ranking uncertainty in multi-agent multi-modal trajectory forecasting.

method Proposes collaborative uncertainty (CU) and a CU-aware regression framework.

result The CU-aware regression framework improves SOTA systems' performances.

uncertainty multi-agent multi-modal trajectory forecasting permutation-equivariant

2022-07-11abs ↗pdf ↗