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A MultiPath Network for Object Detection
[article]
2016
arXiv
pre-print
The recent COCO object detection dataset presents several new challenges for object detection. In particular, it contains objects at a broad range of scales, less prototypical images, and requires more precise localization. To address these challenges, we test three modifications to the standard Fast R-CNN object detector: (1) skip connections that give the detector access to features at multiple network layers, (2) a foveal structure to exploit object context at multiple object resolutions,
arXiv:1604.02135v2
fatcat:567a3x54nbb2zpesp6jv6kv6ie