Deep MANTA: A Coarse-to-fine Many-Task Network for joint 2D and 3D vehicle analysis from monocular image

In this paper, we present a novel approach, called Deep MANTA (Deep Many-Tasks), for many-task vehicle analysis from a given image. A robust convolutional network is introduced for simultaneous vehicle detection, part localization, visibility characterization and 3D dimension estimation... (read more)

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Datasets


Results from the Paper


Ranked #2 on Vehicle Pose Estimation on KITTI Cars Hard (using extra training data)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK USES EXTRA
TRAINING DATA
RESULT BENCHMARK
Vehicle Pose Estimation KITTI Cars Hard Deep-Manta Average Orientation Similarity 80.39 # 2

Methods used in the Paper


METHOD TYPE
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