arXiv (All)
open access
AttentionViG: Cross-Attention-Based Dynamic Neighbor Aggregation in Vision GNNs
Vision Graph Neural Networks (ViGs) have demonstrated promising performance in image recognition tasks against Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs). An essential part of the ViG framework is the node-neighbor feature aggregation method. Although various graph convoluti
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Official Review · ICLR 2024#787141
- Neighbor-Aware Token Reduction via Hilbert Curve for Vision Transformers#1051441
- Preserve, Then Resolve: Many-to-Many Association and Robust Estimation with General-Purpose Visual Features#798868
- Preserve, Then Resolve: Many-to-Many Association and Robust Estimation with General-Purpose Visual Features#797454
- Feature Evolution and Migration during Vision Transformer Training#471236
Record · ID 1117252
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive