Methods › Computer Vision › Convolutional Neural Networks › TResNet

TResNet

1 paper tagged archive 2025-07-28

Introduced by Tal Ridnik et al. in TResNet: High Performance GPU-Dedicated Architecture

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

A TResNet is a variant on a ResNet that aim to boost accuracy while maintaining GPU training and inference efficiency. They contain several design tricks including a SpaceToDepth stem, Anti-Alias downsampling, In-Place Activated BatchNorm, Blocks selection and squeeze-and-excitation layers.

PaperSourceSee Code · mrT23/TResNet

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

9 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
Fine-Grained Image Classification1
GPU1
General Classification1
Image Classification1
MUlTI-LABEL-ClASSIFICATION1
Multi-Label Classification1
Object Detection1
Vocal Bursts Intensity Prediction1
object-detection1

Usage over time archive 2025-07-28

Papers per year tagged with TResNet: 2020 to 2020, peak 1 1 0 2020: 1 paper 2020
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

Convolutional Neural Networks

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