# DORAEMON: A Unified Library for Visual Object Modeling and Representation Learning at Scale

Source: [DORAEMON: A Unified Library for Visual Object Modeling and Representation Learning at Scale](<https://www.sota2.com/research/paper/690d7ced2828b7cc6937cc3c>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-11-08T05:01:25.623Z

Authors: Ke Du, Yimin Peng, Chao Gao, Fan Zhou, Siqiao Xue

Published: 2025-11-06T14:22:51.000Z

## Abstract

DORAEMON is an open-source PyTorch library that unifies visual object modeling and representation learning across diverse scales. A single YAML-driven workflow covers classification, retrieval and metric learning; more than 1000 pretrained backbones are exposed through a timm-compatible interface, together with modular losses, augmentations and distributed-training utilities. Reproducible recipes match or exceed reference results on ImageNet-1K, MS-Celeb-1M and Stanford online products, while one-command export to ONNX or HuggingFace bridges research and deployment. By consolidating datasets, models, and training techniques into one platform, DORAEMON offers a scalable foundation for rapid experimentation in visual recognition and representation learning, enabling efficient transfer of research advances to real-world applications. The repository is available at https://github.com/wuji3/DORAEMON.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2511.04394>)

[PDF](<https://arxiv.org/pdf/2511.04394.pdf>)