Papers with region-level retrieval

1 papers
OLIVE: Object Level In-Context Visual Embeddings (2024.acl-long)

Copied to clipboard

Challenge: Existing vision-language models lack fine-grained object-level understanding and grounding . existing models implicitly align text tokens with image patch tokens, which is ineffective for embedding alignment at the same granularity and introduces noisy spurious background features.
Approach: They propose a method to prompt large language models with in-context visual object vectors . this method allows for controllable object-level reasoning .
Outcome: The proposed method achieves competitive referring object classification and captioning performance while offering zero-shot generalization and robustness to visually challenging contexts.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations