Methods › Computer Vision › Light-weight neural networks › ESPNetv2

ESPNetv2

1 paper tagged archive 2025-07-28

Introduced by Sachin Mehta et al. in ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural Network

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

ESPNetv2 is a convolutional neural network that utilises group point-wise and depth-wise dilated separable convolutions to learn representations from a large effective receptive field with fewer FLOPs and parameters.

PaperSourceSee Code · osmr/imgclsmob

Papers archive 2025-07-28

1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

11 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
General Classification1
Image Classification1
Language Modeling1
Language Modelling1
Object1
Object Detection1
Real-Time Object Detection1
Real-Time Semantic Segmentation1
Semantic Segmentation1
image-classification1
object-detection1

Usage over time archive 2025-07-28

Papers per year tagged with ESPNetv2: 2018 to 2018, peak 1 1 0 2018: 1 paper 2018
Papers per year the archive tags with this method, by the paper's archive date (1 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Light-weight neural networksConvolutional Neural Networks

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