Spatial As Deep: Spatial CNN for Traffic Scene Understanding

17 Dec 2017Xingang PanJianping ShiPing LuoXiaogang WangXiaoou Tang

Convolutional neural networks (CNNs) are usually built by stacking convolutional operations layer-by-layer. Although CNN has shown strong capability to extract semantics from raw pixels, its capacity to capture spatial relationships of pixels across rows and columns of an image is not fully explored... (read more)

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Results from the Paper


#3 best model for Lane Detection on TuSimple (using extra training data)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK USES EXTRA
TRAINING DATA
RESULT LEADERBOARD
Lane Detection CULane SCNN F1 score 71.6 # 3

Results from Other Papers


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK USES EXTRA
TRAINING DATA
SOURCE PAPER COMPARE
Lane Detection TuSimple Spatial CNN Accuracy 96.53% # 3