{"list":"other","total":111,"rows":[{"id":"1512.03385","title":"Deep Residual Learning for Image Recognition","created":"2015-12-10","cited_by_count":52096},{"id":"2010.11929","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","created":"2020-10-22","cited_by_count":30186},{"id":"1706.04599","title":"On Calibration of Modern Neural Networks","created":"2017-06-14","cited_by_count":4960},{"id":"1903.11027","title":"nuScenes: A multimodal dataset for autonomous driving","created":"2019-03-26","cited_by_count":4523},{"id":"1506.02142","title":"Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning","created":"2015-06-06","cited_by_count":4448},{"id":"1706.02413","title":"PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space","created":"2017-06-07","cited_by_count":4401},{"id":"1612.01474","title":"Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles","created":"2016-12-05","cited_by_count":3926},{"id":"1912.04838","title":"Scalability in Perception for Autonomous Driving: Waymo Open Dataset","created":"2019-12-10","cited_by_count":2451},{"id":"1711.03938","title":"CARLA: An Open Urban Driving Simulator","created":"2017-11-10","cited_by_count":2449},{"id":"1610.02136","title":"A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks","created":"2016-10-07","cited_by_count":2385},{"id":"1703.04977","title":"What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?","created":"2017-03-15","cited_by_count":2352},{"id":"1801.07829","title":"Dynamic Graph CNN for Learning on Point Clouds","created":"2018-01-24","cited_by_count":2223},{"id":"1906.02530","title":"Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift","created":"2019-06-06","cited_by_count":1287},{"id":"1904.08755","title":"4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural Networks","created":"2019-04-18","cited_by_count":1208},{"id":"1904.08889","title":"KPConv: Flexible and Deformable Convolution for Point Clouds","created":"2019-04-18","cited_by_count":1205},{"id":"1910.09457","title":"Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods","created":"2019-10-21","cited_by_count":913},{"id":"2011.06225","title":"A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges","created":"2020-11-12","cited_by_count":819},{"id":"1806.01768","title":"Evidential Deep Learning to Quantify Classification Uncertainty","created":"2018-06-05","cited_by_count":732},{"id":"2107.03342","title":"A Survey of Uncertainty in Deep Neural Networks","created":"2021-07-07","cited_by_count":680},{"id":"1911.11236","title":"RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds","created":"2019-11-25","cited_by_count":585},{"id":"1802.10501","title":"Predictive Uncertainty Estimation via Prior Networks","created":"2018-02-28","cited_by_count":557},{"id":"1904.01685","title":"Measuring Calibration in Deep Learning","created":"2019-04-02","cited_by_count":446},{"id":"2007.16100","title":"Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution","created":"2020-07-31","cited_by_count":423},{"id":"2011.10033","title":"Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR Segmentation","created":"2020-11-19","cited_by_count":389},{"id":"2210.05666","title":"Point Transformer V2: Grouped Vector Attention and Partition-based Pooling","created":"2022-10-11","cited_by_count":388},{"id":"2002.06715","title":"BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning","created":"2020-02-17","cited_by_count":371},{"id":"1910.12656","title":"Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with Dirichlet calibration","created":"2019-10-28","cited_by_count":364},{"id":"2110.06207","title":"Open-Set Recognition: a Good Closed-Set Classifier is All You Need?","created":"2021-10-12","cited_by_count":353},{"id":"2003.14032","title":"PolarNet: An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentation","created":"2020-03-31","cited_by_count":275},{"id":"2003.03653","title":"SalsaNext: Fast, Uncertainty-aware Semantic Segmentation of LiDAR Point Clouds for Autonomous Driving","created":"2020-03-07","cited_by_count":226},{"id":"2103.14635","title":"PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds","created":"2021-03-26","cited_by_count":211},{"id":"2002.06470","title":"Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning","created":"2020-02-15","cited_by_count":210},{"id":"1906.01620","title":"Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision","created":"2019-06-04","cited_by_count":182},{"id":"2005.06209","title":"On the uncertainty of self-supervised monocular depth estimation","created":"2020-05-13","cited_by_count":182},{"id":"2301.04926","title":"CLIP2Scene: Towards Label-efficient 3D Scene Understanding by CLIP","created":"2023-01-12","cited_by_count":181},{"id":"2010.06610","title":"Training independent subnetworks for robust prediction","created":"2020-10-13","cited_by_count":177},{"id":"2103.12978","title":"RPVNet: A Deep and Efficient Range-Point-Voxel Fusion Network for LiDAR Point Cloud Segmentation","created":"2021-03-24","cited_by_count":173},{"id":"2004.01803","title":"SqueezeSegV3: Spatially-Adaptive Convolution for Efficient Point-Cloud Segmentation","created":"2020-04-03","cited_by_count":170},{"id":"2109.03805","title":"Panoptic nuScenes: A Large-Scale Benchmark for LiDAR Panoptic Segmentation and Tracking","created":"2021-09-08","cited_by_count":166},{"id":"2102.04530","title":"(AF)2-S3Net: Attentive Feature Fusion with Adaptive Feature Selection for Sparse Semantic Segmentation Network","created":"2021-02-08","cited_by_count":164},{"id":"1911.13273","title":"Confidence Calibration and Predictive Uncertainty Estimation for Deep Medical Image Segmentation","created":"2019-11-29","cited_by_count":163},{"id":"2207.04397","title":"2DPASS: 2D Priors Assisted Semantic Segmentation on LiDAR Point Clouds","created":"2022-07-10","cited_by_count":158},{"id":"1811.12709","title":"Evaluating Bayesian Deep Learning Methods for Semantic Segmentation","created":"2018-11-30","cited_by_count":143},{"id":"2007.08792","title":"Uncertainty Quantification and Deep Ensembles","created":"2020-07-17","cited_by_count":139},{"id":"1802.07095","title":"Uncertainty Estimates and Multi-Hypotheses Networks for Optical Flow","created":"2018-02-20","cited_by_count":135},{"id":"1911.12676","title":"xMUDA: Cross-Modal Unsupervised Domain Adaptation for 3D Semantic Segmentation","created":"2019-11-28","cited_by_count":129},{"id":"2303.17597","title":"Robo3D: Towards Robust and Reliable 3D Perception against Corruptions","created":"2023-03-30","cited_by_count":129},{"id":"2303.05367","title":"Rethinking Range View Representation for LiDAR Segmentation","created":"2023-03-09","cited_by_count":128},{"id":"2306.09347","title":"Segment Any Point Cloud Sequences by Distilling Vision Foundation Models","created":"2023-06-15","cited_by_count":125},{"id":"2002.09147","title":"SemanticPOSS: A Point Cloud Dataset with Large Quantity of Dynamic Instances","created":"2020-02-21","cited_by_count":123},{"id":"2103.14962","title":"Panoptic-PolarNet: Proposal-free LiDAR Point Cloud Panoptic Segmentation","created":"2021-03-27","cited_by_count":107},{"id":"2006.06015","title":"Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty","created":"2020-06-10","cited_by_count":101},{"id":"2004.13546","title":"Multivariate Confidence Calibration for Object Detection","created":"2020-04-28","cited_by_count":98},{"id":"2108.05249","title":"Fog Simulation on Real LiDAR Point Clouds for 3D Object Detection in Adverse Weather","created":"2021-08-11","cited_by_count":97},{"id":"2008.05105","title":"Local Temperature Scaling for Probability Calibration","created":"2020-08-12","cited_by_count":95},{"id":"2207.00026","title":"LaserMix for Semi-Supervised LiDAR Semantic Segmentation","created":"2022-06-30","cited_by_count":93},{"id":"2012.04934","title":"AMVNet: Assertion-based Multi-View Fusion Network for LiDAR Semantic Segmentation","created":"2020-12-09","cited_by_count":87},{"id":"2011.11964","title":"LiDAR-based Panoptic Segmentation via Dynamic Shifting Network","created":"2020-11-24","cited_by_count":84},{"id":"2102.08009","title":"EfficientLPS: Efficient LiDAR Panoptic Segmentation","created":"2021-02-16","cited_by_count":76},{"id":"2301.10222","title":"RangeViT: Towards Vision Transformers for 3D Semantic Segmentation in Autonomous Driving","created":"2023-01-24","cited_by_count":76},{"id":"2208.00223","title":"PolarMix: A General Data Augmentation Technique for LiDAR Point Clouds","created":"2022-07-30","cited_by_count":74},{"id":"2203.15118","title":"LiDAR Snowfall Simulation for Robust 3D Object Detection","created":"2022-03-28","cited_by_count":73},{"id":"2204.10319","title":"TorchSparse: Efficient Point Cloud Inference Engine","created":"2022-04-21","cited_by_count":73},{"id":"2202.03377","title":"Benchmarking and Analyzing Point Cloud Classification under Corruptions","created":"2022-02-07","cited_by_count":70},{"id":"2203.08537","title":"Scribble-Supervised LiDAR Semantic Segmentation","created":"2022-03-16","cited_by_count":69},{"id":"2002.09103","title":"Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation","created":"2020-02-21","cited_by_count":61},{"id":"2308.09711","title":"Robust Monocular Depth Estimation under Challenging Conditions","created":"2023-08-18","cited_by_count":58},{"id":"2309.05573","title":"UniSeg: A Unified Multi-Modal LiDAR Segmentation Network and the OpenPCSeg Codebase","created":"2023-09-11","cited_by_count":57},{"id":"2207.12691","title":"CENet: Toward Concise and Efficient LiDAR Semantic Segmentation for Autonomous Driving","created":"2022-07-26","cited_by_count":56},{"id":"2202.13589","title":"Unsupervised Point Cloud Representation Learning with Deep Neural Networks: A Survey","created":"2022-02-28","cited_by_count":54},{"id":"2306.03899","title":"Towards Label-free Scene Understanding by Vision Foundation Models","created":"2023-06-06","cited_by_count":54},{"id":"2301.10100","title":"Using a Waffle Iron for Automotive Point Cloud Semantic Segmentation","created":"2023-01-24","cited_by_count":53},{"id":"2205.14951","title":"Benchmarking the Robustness of LiDAR-Camera Fusion for 3D Object Detection","created":"2022-05-30","cited_by_count":50},{"id":"2312.04484","title":"FRNet: Frustum-Range Networks for Scalable LiDAR Segmentation","created":"2023-12-07","cited_by_count":50},{"id":"2210.09184","title":"Packed-Ensembles for Efficient Uncertainty Estimation","created":"2022-10-17","cited_by_count":49},{"id":"2310.15171","title":"RoboDepth: Robust Out-of-Distribution Depth Estimation under Corruptions","created":"2023-10-23","cited_by_count":49},{"id":"2106.02377","title":"A Survey on Deep Domain Adaptation for LiDAR Perception","created":"2021-06-04","cited_by_count":47},{"id":"2109.03787","title":"FIDNet: LiDAR Point Cloud Semantic Segmentation with Fully Interpolation Decoding","created":"2021-09-08","cited_by_count":46},{"id":"2304.00690","title":"3D Semantic Segmentation in the Wild: Learning Generalized Models for Adverse-Condition Point Clouds","created":"2023-04-03","cited_by_count":46},{"id":"2304.06719","title":"RoboBEV: Towards Robust Bird's Eye View Perception under Corruptions","created":"2023-04-13","cited_by_count":42},{"id":"2312.02158","title":"PaSCo: Urban 3D Panoptic Scene Completion with Uncertainty Awareness","created":"2023-12-04","cited_by_count":42},{"id":"2111.15242","title":"ConDA: Unsupervised Domain Adaptation for LiDAR Segmentation via Regularized Domain Concatenation","created":"2021-11-30","cited_by_count":41},{"id":"1511.03243","title":"Black-box $\\alpha$-divergence Minimization","created":"2015-11-10","cited_by_count":37},{"id":"2207.02605","title":"GFNet: Geometric Flow Network for 3D Point Cloud Semantic Segmentation","created":"2022-07-06","cited_by_count":36},{"id":"2311.12862","title":"TorchSparse++: Efficient Training and Inference Framework for Sparse Convolution on GPUs","created":"2023-10-25","cited_by_count":36},{"id":"2207.09763","title":"GIPSO: Geometrically Informed Propagation for Online Adaptation in 3D LiDAR Segmentation","created":"2022-07-20","cited_by_count":35},{"id":"2105.04290","title":"Meta-Cal: Well-controlled Post-hoc Calibration by Ranking","created":"2021-05-10","cited_by_count":33},{"id":"2209.07601","title":"Towards Improving Calibration in Object Detection Under Domain Shift","created":"2022-09-15","cited_by_count":26},{"id":"2212.12053","title":"On Calibrating Semantic Segmentation Models: Analyses and An Algorithm","created":"2022-12-22","cited_by_count":25},{"id":"2207.06873","title":"BayesCap: Bayesian Identity Cap for Calibrated Uncertainty in Frozen Neural Networks","created":"2022-07-14","cited_by_count":23},{"id":"2212.10230","title":"A Comprehensive Study of the Robustness for LiDAR-based 3D Object Detectors against Adversarial Attacks","created":"2022-12-20","cited_by_count":22},{"id":"2310.08820","title":"Learning to Adapt SAM for Segmenting Cross-domain Point Clouds","created":"2023-10-13","cited_by_count":20},{"id":"2307.00934","title":"Towards Building Self-Aware Object Detectors via Reliable Uncertainty Quantification and Calibration","created":"2023-07-03","cited_by_count":19},{"id":"2308.11990","title":"RankMixup: Ranking-Based Mixup Training for Network Calibration","created":"2023-08-23","cited_by_count":19},{"id":"2312.12144","title":"M-BEV: Masked BEV Perception for Robust Autonomous Driving","created":"2023-12-19","cited_by_count":19},{"id":"2106.07545","title":"PolarStream: Streaming Lidar Object Detection and Segmentation with Polar Pillars","created":"2021-06-14","cited_by_count":18},{"id":"2301.00970","title":"Benchmarking the Robustness of LiDAR Semantic Segmentation Models","created":"2023-01-03","cited_by_count":18},{"id":"2302.04002","title":"The Devil is in the Wrongly-classified Samples: Towards Unified Open-set Recognition","created":"2023-02-08","cited_by_count":16},{"id":"2204.09914","title":"CPGNet: Cascade Point-Grid Fusion Network for Real-Time LiDAR Semantic Segmentation","created":"2022-04-21","cited_by_count":15},{"id":"2301.10766","title":"On the Adversarial Robustness of Camera-based 3D Object Detection","created":"2023-01-25","cited_by_count":15}],"next_cursor":"100"}