Submitted by Angela Dai.

Submission data

Full nameENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
Descriptionreimplementation based from https://github.com/e-lab/ENet-training
Publication titleENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
Publication authorsRe-implementation of Adam Paszke, Abhishek Chaurasia, Sangpil Kim, Eugenio Culurciello
Publication URLhttps://arxiv.org/abs/1606.02147
Input Data TypesUses Color        Uses 2D
Programming language(s)pytorch
HardwareGTX 1080
Submission creation date13 Jul, 2018
Last edited17 Jul, 2018

2D semantic label results

Infoavg ioubathtubbedbookshelfcabinetchaircountercurtaindeskdoorfloorotherfurniturepicturerefrigeratorshower curtainsinksofatabletoiletwallwindow
0.3760.2640.4520.4520.3650.1810.1430.4560.4090.3460.7690.1640.2180.3590.1230.4030.3810.3130.5710.6850.472