- How Do Neural Networks See Depth in Single Images? [Notes] ICCV 2019
- Self-supervised Sparse-to-Dense: Self-supervised Depth Completion from LiDAR and Monocular Camera ICRA 2019 (depth completion)
- DC: Depth Coefficients for Depth Completion [Notes] CVPR 2019 (Xiaoming Liu)
- Parse Geometry from a Line: Monocular Depth Estimation with Partial Laser Observation [Notes] ICRA 2017
- PointPainting: Sequential Fusion for 3D Object Detection (nuscenece)
- VO-Monodepth: Enhancing self-supervised monocular depth estimation with traditional visual odometry [Notes] 3DV 2019 (sparse to dense)
- Probabilistic Object Detection: Definition and Evaluation [Notes]
- The Fishyscapes Benchmark: Measuring Blind Spots in Semantic Segmentation [Notes] ICCV 2019
- On Calibration of Modern Neural Networks [Notes] ICML 2017 (Weinberger)
- Extreme clicking for efficient object annotation [Notes] ICCV 2017
- Radar and Camera Early Fusion for Vehicle Detection in Advanced Driver Assistance Systems [Notes] NeurIPS 2019 (radar)
- Deep Active Learning for Efficient Training of a LiDAR 3D Object Detector [Notes] IV 2019
- C3DPO: Canonical 3D Pose Networks for Non-Rigid Structure From Motion [Notes] ICCV 2019
- YOLACT: Real-time Instance Segmentation [Notes] ICCV 2019
- YOLACT++: Better Real-time Instance Segmentation
- Review of Image and Feature Descriptors
- Vehicle Detection With Automotive Radar Using Deep Learning on Range-Azimuth-Doppler Tensors [Notes] ICCV 2019
- GPP: Ground Plane Polling for 6DoF Pose Estimation of Objects on the Road [Notes] (UCSD, mono 3DOD)
- MVRA: Multi-View Reprojection Architecture for Orientation Estimation [Notes] ICCV 2019
- YOLOv3: An Incremental Improvement
- Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty for Autonomous Driving [Notes] ICCV 2019 (Detection with Uncertainty)
- Bayesian YOLOv3: Uncertainty Estimation in One-Stage Object Detection [Notes] (DriveU)
- Towards Safe Autonomous Driving: Capture Uncertainty in the Deep Neural Network For Lidar 3D Vehicle Detection [Notes] ITSC 2018 (DriveU)
- Leveraging Heteroscedastic Aleatoric Uncertainties for Robust Real-Time LiDAR 3D Object Detection [Notes] IV 2019 (DriveU)
- Can We Trust You? On Calibration of a Probabilistic Object Detector for Autonomous Driving [Notes] IROS 2019 (DriveU)
- LaserNet: An Efficient Probabilistic 3D Object Detector for Autonomous Driving [Notes] CVPR 2019 (uncertainty)
- LaserNet KL: Learning an Uncertainty-Aware Object Detector for Autonomous Driving [Notes] (LaserNet with KL divergence)
- IoUNet: Acquisition of Localization Confidence for Accurate Object Detection [Notes] ECCV 2018
- gIoU: Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression [Notes] CVPR 2019
- KL Loss: Bounding Box Regression with Uncertainty for Accurate Object Detection [Notes] CVPR 2019
- CAM-Convs: Camera-Aware Multi-Scale Convolutions for Single-View Depth [Notes] CVPR 2019
- BayesOD: A Bayesian Approach for Uncertainty Estimation in Deep Object Detectors [Notes]
- TW-SMNet: Deep Multitask Learning of Tele-Wide Stereo Matching [Notes] ICIP 2019
- Accurate Uncertainties for Deep Learning Using Calibrated Regression [Notes] ICML 2018
- Calibrating Uncertainties in Object Localization Task [Notes] NIPS 2018
- SMWA: On the Over-Smoothing Problem of CNN Based Disparity Estimation [Notes] ICCV 2019 (depth estimation)
- Sparse-to-Dense: Depth Prediction from Sparse Depth Samples and a Single Image [Notes] ICRA 2018 (depth completion)
- Review of monocular object detection
- Review of 2D 3D contraints in Mono 3DOD
- MonoGRNet 2: Monocular 3D Object Detection via Geometric Reasoning on Keypoints [Notes] (estimates depth from keypoints)
- Deep MANTA: A Coarse-to-fine Many-Task Network for joint 2D and 3D vehicle analysis from monocular image [Notes] CVPR 2017
- SS3D: Monocular 3D Object Detection and Box Fitting Trained End-to-End Using Intersection-over-Union Loss [Notes] (rergess distance from images, centernet like)
- GS3D: An Efficient 3D Object Detection Framework for Autonomous Driving [Notes] CVPR 2019
- M3D-RPN: Monocular 3D Region Proposal Network for Object Detection [Notes] ICCV 2019 (Xiaoming Liu)
- TLNet: Triangulation Learning Network: from Monocular to Stereo 3D Object Detection [Notes] CVPR 2019
- A Survey on 3D Object Detection Methods for Autonomous Driving Applications [Notes] (Review) TITS 2019
- BEV-IPM: Deep Learning based Vehicle Position and Orientation Estimation via Inverse Perspective Mapping Image [Notes] IV 2019
- ForeSeE: Task-Aware Monocular Depth Estimation for 3D Object Detection [Notes] (successor to pseudo-lidar) (mono 3DOD SOTA)
- Obj-dist: Learning Object-specific Distance from a Monocular Image [Notes] ICCV 2019 (xmotors.ai + NYU)
- DisNet: A novel method for distance estimation from monocular camera [Notes] IROS 2018
- BirdGAN: Learning 2D to 3D Lifting for Object Detection in 3D for Autonomous Vehicles [Notes] IROS 2019
- Shift R-CNN: Deep Monocular 3D Object Detection with Closed-Form Geometric Constraints [Notes] ICIP 2019
- 3D-RCNN: Instance-level 3D Object Reconstruction via Render-and-Compare [Notes] CVPR 2018
- Deep Optics for Monocular Depth Estimation and 3D Object Detection [Notes] ICCV 2019
- MonoLoco: Monocular 3D Pedestrian Localization and Uncertainty Estimation [Notes] ICCV 2019
- Joint Monocular 3D Vehicle Detection and Tracking [Notes] ICCV 2019 (Berkeley DeepDrive)
- CasGeo: 3D Bounding Box Estimation for Autonomous Vehicles by Cascaded Geometric Constraints and Depurated 2D Detections Using 3D Results [Notes]
- Slimmable Neural Networks [Notes] ICLR 2019
- Universally Slimmable Networks and Improved Training Techniques [Notes] ICCV 2019
- AutoSlim: Towards One-Shot Architecture Search for Channel Numbers
- Once for All: Train One Network and Specialize it for Efficient Deployment
- DOTA: A Large-scale Dataset for Object Detection in Aerial Images [Notes] CVPR 2018 (rotated bbox)
- RoiTransformer: Learning RoI Transformer for Oriented Object Detection in Aerial Images [Notes] CVPR 2019 (rotated bbox)
- RRPN: Arbitrary-Oriented Scene Text Detection via Rotation Proposals TMM 2018
- R2CNN: Rotational Region CNN for Orientation Robust Scene Text Detection (rotated bbox)
- TI white paper: Webinar: mmWave Radar for Automotive and Industrial applications [Notes] (TI, radar)
- Federated Learning: Strategies for Improving Communication Efficiency [Notes] NIPS 2016
- sort: Simple Online and Realtime Tracking [Notes] ICIP 2016
- deep-sort: Simple Online and Realtime Tracking with a Deep Association Metric [Notes]
- MT-CNN: Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks [Notes] SPL 2016 (real time, facial landmark)
- RetinaFace: Single-stage Dense Face Localisation in the Wild [Notes] (joint object and landmark detection)
- Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video [Notes] NIPS 2019
- SiamMask: Fast Online Object Tracking and Segmentation: A Unifying Approach CVPR 2019 (tracking, segmentation, label propagation)
- Detect to Track and Track to Detect ICCV 2017 (from Christoph Feichtenhofer)
- Review of Kálmán Filter (from Tim Babb, Pixar Animation) [Notes]
- R-FCN: Object Detection via Region-based Fully Convolutional Networks [Notes] NIPS 2016
- Guided backprop: Striving for Simplicity: The All Convolutional Net [Notes] ICLR 2015
- Occlusion-Net: 2D/3D Occluded Keypoint Localization Using Graph Networks [Notes] CVPR 2019
- Boxy Vehicle Detection in Large Images [Notes] ICCV 2019
- FQNet: Deep Fitting Degree Scoring Network for Monocular 3D Object Detection [Notes] CVPR 2019 (Mono 3DOD, Jiwen Lu)
- Mono3D: Monocular 3D Object Detection for Autonomous Driving [Notes] CVPR2016
- MonoDIS: Disentangling Monocular 3D Object Detection [Notes] ICCV 2019
- Pseudo lidar-e2e: Monocular 3D Object Detection with Pseudo-LiDAR Point Cloud [Notes] ICCV 2019 (pseudo-lidar with 2d and 3d consistency loss, better than PL and worse than PL++, SOTA for pure mono3D)
- MonoGRNet: A Geometric Reasoning Network for Monocular 3D Object Localization [Notes] AAAI 2019 (SOTA of Mono3DOD, MLF < MonoGRNet < Pseudo-lidar)
- MLF: Multi-Level Fusion based 3D Object Detection from Monocular Images [Notes] CVPR 2018 (precursor to pseudo-lidar)
- ROI-10D: Monocular Lifting of 2D Detection to 6D Pose and Metric Shape [Notes] CVPR 2019
- Accurate Monocular 3D Object Detection via Color-Embedded 3D Reconstruction for Autonomous Driving [Notes] (similar to pseudo-lidar, color-enhanced) ICCV 2019
- Mono3D++: Monocular 3D Vehicle Detection with Two-Scale 3D Hypotheses and Task Priors [Notes] (from Stefano Soatto) AAAI 2019
- Deep Metadata Fusion for Traffic Light to Lane Assignment [Notes] IEEE RA-L 2019 (traffic lights association)
- Automatic Traffic Light to Ego Vehicle Lane Association at Complex Intersections ITSC 2019 (traffic lights association)
- Distant Vehicle Detection Using Radar and Vision [Notes] ICRA 2019 (radar, vision, radar tracklets fusion)
- Distance Estimation of Monocular Based on Vehicle Pose Information [Notes]
- Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics [Notes] CVPR 2018 (Alex Kendall)
- GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks [Notes] ICML 2018 (multitask)
- DTP: Dynamic Task Prioritization for Multitask Learning [Notes] ECCV 2018 (multitask)
- Will this car change the lane? - Turn signal recognition in the frequency domain [Notes] IV 2014
- Complex-YOLO: Real-time 3D Object Detection on Point Clouds [Notes] (BEV detection only)
- Complexer-YOLO: Real-Time 3D Object Detection and Tracking on Semantic Point Clouds CVPR 2019 (sensor fusion and tracking)
- An intriguing failing of convolutional neural networks and the CoordConv solution [Notes] NIPS 2018
- Deep Parametric Continuous Convolutional Neural Networks [Notes] CVPR 2018 (@Uber, sensor fusion)
- ContFuse: Deep Continuous Fusion for Multi-Sensor 3D Object Detection [Notes] ECCV 2018 (@Uber, sensor fusion, birds eye view)
- Fast and Furious: Real Time End-to-End 3D Detection, Tracking and Motion Forecasting with a Single Convolutional Net [Notes] CVPR 2018 oral (lidar only, perception and prediction)
- Depth from Videos in the Wild: Unsupervised Monocular Depth Learning from Unknown Cameras [Notes] ICCV 2019 (monocular depth estimation, intrinsic estimation, SOTA)
- monodepth: Unsupervised Monocular Depth Estimation with Left-Right Consistency [Notes] CVPR 2017 oral (monocular depth estimation, stereo for training)
- Struct2depth: Depth Prediction Without the Sensors: Leveraging Structure for Unsupervised Learning from Monocular Videos [Notes] AAAI 2019 (monocular depth estimation, estimating movement of dynamic object)
- Unsupervised Learning of Geometry with Edge-aware Depth-Normal Consistency [Notes] AAAI 2018 (monocular depth estimation, static assumption, surface normal)
- LEGO Learning Edge with Geometry all at Once by Watching Videos [Notes] CVPR 2018 spotlight (monocular depth estimation, static assumption, surface normal)
- Object Detection and 3D Estimation via an FMCW Radar Using a Fully Convolutional Network [Notes] (radar, RD map, OD, Arxiv 201902)
- A study on Radar Target Detection Based on Deep Neural Networks [Notes] (radar, RD map, OD)
- 2D Car Detection in Radar Data with PointNets [Notes] (from Ulm Univ, radar, point cloud, OD, Arxiv 201904)
- Learning Confidence for Out-of-Distribution Detection in Neural Networks [Notes] (budget to cheat)
- A Deep Learning Approach to Traffic Lights: Detection, Tracking, and Classification [Notes] ICRA 2017 (Bosch, traffic lights)
- How hard can it be? Estimating the difficulty of visual search in an image [Notes] CVPR 2016
- Deep Multi-modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges [Notes] (review from Bosch)
- Review of monocular 3d object detection (blog from 知乎)
- Deep3dBox: 3D Bounding Box Estimation Using Deep Learning and Geometry [Notes] (from Zoox) CVPR 2017
- MonoPSR: Monocular 3D Object Detection Leveraging Accurate Proposals and Shape Reconstruction [Notes] CVPR 2019
- OFT: Orthographic Feature Transform for Monocular 3D Object Detection [Notes] (Convert camera to BEV, Alex Kendall) BMVC 2019