Searching for Efficient Multi-Scale Architectures for Dense Image Prediction

NeurIPS 2018 Liang-Chieh ChenMaxwell D. CollinsYukun ZhuGeorge PapandreouBarret ZophFlorian SchroffHartwig AdamJonathon Shlens

The design of neural network architectures is an important component for achieving state-of-the-art performance with machine learning systems across a broad array of tasks. Much work has endeavored to design and build architectures automatically through clever construction of a search space paired with simple learning algorithms... (read more)

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Results from the Paper


Ranked #3 on Semantic Segmentation on PASCAL VOC 2012 test (using extra training data)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK USES EXTRA
TRAINING DATA
RESULT BENCHMARK
Semantic Segmentation Cityscapes test Dense Prediction Cell Mean IoU (class) 82.7% # 13
Human Part Segmentation PASCAL-Person-Part DPC mIoU 71.34 # 3
Semantic Segmentation PASCAL VOC 2012 test DPC Mean IoU 87.9% # 3

Methods used in the Paper


METHOD TYPE
🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet