Methods › Computer Vision › Vision and Language Pre-Trained Models › UNIMO

UNIMO

4 papers tagged archive 2025-07-28

Introduced by Wei Li et al. in UNIMO: Towards Unified-Modal Understanding and Generation via Cross-Modal Contrastive Learning

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

UNIMO is a multi-modal pre-training architecture that can effectively adapt to both single modal and multimodal understanding and generation tasks. UNIMO learns visual representations and textual representations simultaneously, and unifies them into the same semantic space via cross-modal contrastive learning (CMCL) based on a large-scale corpus of image collections, text corpus and image-text pairs. The CMCL aligns the visual representation and textual representation, and unifies them into the same semantic space based on image-text pairs.

Paper Source

Papers archive 2025-07-28

4 shown of 4, 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.

WuDaoMM: A large-scale Multi-Modal Dataset for Pre-training models
22 Mar 2022 · 0 repositories · arXiv:2203.11480
UNIMO-2: End-to-End Unified Vision-Language Grounded Learning
17 Mar 2022 · 1 repository · arXiv:2203.09067
A Multimodal Sentiment Dataset for Video Recommendation
17 Sep 2021 · 0 repositories · arXiv:2109.08333
UNIMO: Towards Unified-Modal Understanding and Generation via Cross-Modal Contrastive Learning
31 Dec 2020 · 3 repositories · arXiv:2012.15409

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.

Task	Papers
Image Captioning	2
Contrastive Learning	1
Cross-Modal Retrieval	1
Image Generation	1
Multimodal Sentiment Analysis	1
Question Answering	1
Sentiment Analysis	1
Text to Image Generation	1
Text-to-Image Generation	1
Video Understanding	1
Visual Question Answering (VQA)	1

Usage over time archive 2025-07-28

Papers per year the archive tags with this method, by the paper's archive date (4 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

Vision and Language Pre-Trained Models Multi-Modal Methods

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