The CVC Partial Occlusion Virtual Pedestrian datasets (CVC-01 to CVC-06) cover a range of scenarios of occluded pedestrians generated in a virtual and real environment. See link for more details, overview here: CVC-06 PARTIALLY OCCLUDED VIRTUAL PEDESTRIAN DATASET 2400 and 2414 cropped pedestrians (with their corresponding horizontal mirrors) from Half-Life 2 CVC-05 PARTIALLY OCCLUDED PEDESTRIAN DATASET 593 positive frames with annotated pedestrians (with their corresponding horizontal mirrors). CVC-04 VIRTUAL PEDESTRIAN DATASET 2 1208 virtual pedestrians (with their corresponding horizontal mirrors) and 6828 pedestrian-free background images to extract negatives for training from Half-life 2 CVC-03 VIRTUAL PEDESTRIAN DATASET - 1678 virtual pedestrians (with their corresponding horizontal mirrors) and 2048 pedestrian-free background from Half-Life 2 CVC-02 PEDESTRIAN DATASET - CVC-02-CG (Candidate Generation): 100 frames in color, depth and 3D points information. - CVC-02-Classification: training (1016 cropped positives and mirrors, 7650 cropped negatives and pedestrian-free images), testing set (window-based, with 570 cropped positives and mirrors, 7500 cropped negatives and pedestrian-free images) and testing set (image-based, with 250 frames containing 587 annotated pedestrians). - CVC-02-System: 15 sequences of 4364 frames, 7983 pedestrian annotations. CVC-01 PEDESTRIAN DATASET - 1000 manually annotated pedestrians (plus 1000 mirrors) - 6175 random non-pedestrians windows from the road area - Original scale PNG files

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