A survey of occlusion handling in object detection/recognition
- 遮挡目标检测与识别技术研究_蔡星艳
- Occlusion Detection and Handling: A Review
- Occlusion Handling in Generic Object Detection: A Review
- Survey of pedestrian detection with occlusion
- [CVPR2006] The layout consistent random field for recognizing and segmenting partially occluded objects
- [CVPR2011] A segmentation-aware object detection model with occlusion handling
- [CVIU2013] Occlusion cues for image scene layering
- [IV2013] Occlusion handling using discriminative model of trained part templates and conditional random field
- [ICANN2013] Using the Analytic Feature Framework for the Detection of Occluded Objects
- [ICANN2014] A two-stage classifier architecture for detecting objects under real-world occlusion patterns
- [BMVC2016] Measuring the effect of nuisance variables on classifiers
- [ECCV2016] Amodal instance segmentation
- [2017] Detecting semantic parts on partially occluded objects
- [2017] Improved regularization of convolutional neural networks with cutout
- [CVPR2017] A-fast-rcnn: Hard positive generation via adversary for object detection
- [CVPR2018] Segan: Segmenting and generating the invisible
- 提出DYCE数据集
- [CVPR2018] Deepvoting: A robust and explainable deep network for semantic part detection under partial occlusion
- [2019] Robustness of Object Recognition under Extreme Occlusion in Humans and Computational Models
- [2019] Tdapnet: Prototype network with recurrent top-down attention for robust object classification under partial occlusion
- [CVPR2019] Amodal instance segmentation with kins dataset
- 提出KITTI数据集,针对amodal实例分割任务
- [WACV2019] Learning to see the invisible: End-to-end trainable amodal instance segmentation
- [IJCV2020] Deep Learning for Generic Object Detection: A Survey
- 只提到了一点关于occlusion
- [CVPR2020] Robust object detection under occlusion with context-aware compositionalnets
- 提出新遮挡数据集 OccludedCOCO
- [CVPR2020] Self-supervised scene de-occlusion
- [IJCV2021] Compositional convolutional neural networks: A robust and interpretable model for object recognition under occlusion
- [ICCV2009] An HOG-LBP human detector with partial occlusion handling
- [CVPR2010] Multi-cue pedestrian classification with partial occlusion handling
- [ICCV2015] Deep learning strong parts for pedestrian detection
- [ECCV2018] Occlusion-aware R-CNN: detecting pedestrians in a crowd
- [CVPR2018] Repulsion Loss: Detecting Pedestrians in a Crowd
- [TITS2019] Overcoming Occlusion in the Automotive Environment—A Review
- [2021] Survey of pedestrian detection with occlusion
- [TPAMI2017] Faceness-net: Face detection through deep facial part responses
- [ICMR2020] Occlusion-Aware GAN for Face De-Occlusion in the Wild
- [2020] A survey of face recognition techniques under occlusion
- [TITS2008] Multilevel Framework to Detect and Handle Vehicle Occlusion
- [SP2015] Inferring occluded features for fast object detection
- [CVPR2019] Occlusion-Net: 2D/3D Occluded Keypoint Localization Using Graph Networks
- [WACV2020] Combining Compositional Models and Deep Networks For Robust Object Classification under Occlusion
- 提出数据集Occluded-Vehicles
- [CVPR2020] Compositional Convolutional Neural Networks: A Deep Architecture with Innate Robustness to Partial Occlusion [Code]
- 使用数据集Occluded-Vehicles
- [CVPR2001] Handling occlusions in dense multi-view stereo
- [CVPR2005] Symmetric stereo matching for occlusion handling
- [BMVC2018] Symmnet: A symmetric convolutional neural network for occlusion detection
- [ICPR2004] Tracking people through occlusions
- [CVPR2005] Real-time multiple objects tracking with occlusion handling in dynamic scenes
- [CVPR2007] Robust Occlusion Handling in Object Tracking
- [ICME2014] Multi-person tracking-by-detection with local particle filtering and global occlusion handling
- [TC2017] Towards occlusion handling: object tracking with background estimation
- [TMM2018] Context-aware three-dimensional mean-shift with occlusion handling for robust object tracking in RGB-D videos
- [2020] A Bayesian Filter for Multi-view 3D Multi-object Tracking with Occlusion Handling
- [CVPR2011] Monocular 3D scene understanding with explicit occlusion reasoning
- [CVPR2013] Explicit occlusion modeling for 3d object class representations
- [IROS2018] Instance segmentation of visible and occluded regions for finding and picking target from a pile of objects
- [3DV2018] Seethrough: Finding objects in heavily occluded indoor scene images
- [IROS2019] Seeing behind things: Extending semantic segmentation to occluded regions