计算机视觉(目标检测)的一些相关代码和数据库
本文主要记录代码和数据库的一些资源,以便用时方便查找
1.行人检测
转载来源:http://hi.baidu.com/susongzhi/item/085983081b006311eafe38e7
Related Papers:
2014_ECCV_30Hz Object Detection with DPM V5
2014_ECCV_Knowing a good HOG filter whenyou see it: Efficient selection of filters for detection
2014_ECCV_Unsupervised Dense ObjectDiscovery, Detection, Tracking and Reconstruction
2014_ECCV_Comparing Salient ObjectDetection Results without Ground Truth
2014_ECCV_RGBD Salient Object Detection: ABenchmark and Algorithms
2014_ECCV_Saliency Detection with Flash andNo-flash Image Pairs
2014_ECCV_Object Co-Detection via EfficientInference in a Fully-Connected CRF
2014_ECCV_Context as Supervisory Signal:Discovering Objects with Predictable Contex
2014_ECCV_Object Detection and ViewpointEstimation with Auto-masking Neural Network
2014_ECCV_Deep Learning of Scene-specificClassifier for Pedestrian Detection
2014_ECCV_Spatio-Temporal Object DetectionProposals
2014_ECCV_Strengthening the Effectivenessof Pedestrian Detection with Spatially Pooled Features
2014_ECCV_Video Object Discovery andCo-segmentation with Extremely Weak Supervision
2014_ECCV_Face detection without bells andwhistles
2014_ECCV_Human Detection using LearnedPart Alphabet and Pose Dictionary
2014_ECCV_SPADE: Scalar Product Acceleratorby Integer Decomposition for Object Detection
2014_ECCV_Towards UnifiedObject Detection and Segmentation
2014_ECCV_Depth Based Object Detection fromPartial Pose Estimation of Symmetric Objects
2014_ECCV_Training Deformable Object Modelsfor Human Detection based on Alignment and Clustering
2014_ECCV_Spatio-temporal Matching forHuman Detection in Video
2014_ECCV_Facial Landmark Detection by DeepMulti-task Learning
2014_ECCV_Latent-Class Hough Forests for 3DObject Detection and Pose Estimation
2014_ECCV_GIS-assisted Object Detection andgeospatial localization
2014_ECCV_Sliding Shapes for 3D Object Detectionin Depth Images
2014_ECCV_Integrating Context and Occlusionfor Car Detection by Hierarchical And-Or Model
2014_ECCV_Simultaneous Detection andSegmentation
2014_ECCV_Learning Rich Features from RGB-DImages for Object Detection and Segmentation
2014_ITS_Toward real-time pedestrian detection based on a deformable template model
2014_PAMI_Scene-specific pedestrian detection for static video surveillance
2014_CVPR_Switchable Deep Network for Pedestrian Detection
2014_CVPR_Informed Haar-like Features Improve Pedestrian Detection
2013_BMVC_Surveillance camera autocalibration based on pedestrian height distribution
2013_Virtual and real world adaptation for pedestrian detection
2013_CVPR_Robust Multi-Resolution Pedestrian Detection in Traffic Scenes
2. Real-time Pedestrian Detection. Jianxin Wu实现的快速行人检测方法。
4. HIKSVM, HOG+LBP+HIKSVM, 行人检测的经典方法.
7. POM: Probabilistic Occupancy Map. Multiple camera pedestrian detection.
8. Pitor Dollar Detector. Integral Channel Feature + 多尺度特征近似+多特征融合. Real-Time!
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