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Found 5 papers, 1 papers with code
DocKD: Knowledge Distillation from LLMs for Open-World Document Understanding Models
Visual document understanding (VDU) is a challenging task that involves understanding documents across various modalities (text and image) and layouts (forms, tables, etc.).
RAVEN: Multitask Retrieval Augmented Vision-Language Learning
This paper introduces RAVEN, a multitask retrieval augmented VLM framework that enhances base VLMs through efficient, task specific fine-tuning.
DocTr: Document Transformer for Structured Information Extraction in Documents
We present a new formulation for structured information extraction (SIE) from visually rich documents.
Ranked #4 on
Entity Linking
on FUNSD
PolyFormer: Referring Image Segmentation as Sequential Polygon Generation
In this work, instead of directly predicting the pixel-level segmentation masks, the problem of referring image segmentation is formulated as sequential polygon generation, and the predicted polygons can be later converted into segmentation masks.
Ranked #1 on
Referring Expression Segmentation
on ReferIt
(using extra training data)
A Multimodal, Full-Surround Vehicular Testbed for Naturalistic Studies and Benchmarking: Design, Calibration and Deployment
Recent progress in autonomous and semi-autonomous driving has been made possible in part through an assortment of sensors that provide the intelligent agent with an enhanced perception of its surroundings.
