Search Results for author:
Found 7 papers, 4 papers with code
OmniParser: A Unified Framework for Text Spotting, Key Information Extraction and Table Recognition
Recently, visually-situated text parsing (VsTP) has experienced notable advancements, driven by the increasing demand for automated document understanding and the emergence of Generative Large Language Models (LLMs) capable of processing document-based questions.
DD-RobustBench: An Adversarial Robustness Benchmark for Dataset Distillation
Dataset distillation is an advanced technique aimed at compressing datasets into significantly smaller counterparts, while preserving formidable training performance.
Modeling Entities as Semantic Points for Visual Information Extraction in the Wild
As the first contribution of this work, we curate and release a new dataset for VIE, in which the document images are much more challenging in that they are taken from real applications, and difficulties such as blur, partial occlusion, and printing shift are quite common.
Vision-Language Pre-Training for Boosting Scene Text Detectors
In this paper, we specifically adapt vision-language joint learning for scene text detection, a task that intrinsically involves cross-modal interaction between the two modalities: vision and language, since text is the written form of language.
YOLOP: You Only Look Once for Panoptic Driving Perception
A panoptic driving perception system is an essential part of autonomous driving.
Ranked #3 on
Drivable Area Detection
on BDD100K val
MOST: A Multi-Oriented Scene Text Detector with Localization Refinement
Over the past few years, the field of scene text detection has progressed rapidly that modern text detectors are able to hunt text in various challenging scenarios.
Progressive and Aligned Pose Attention Transfer for Person Image Generation
This paper proposes a new generative adversarial network for pose transfer, i. e., transferring the pose of a given person to a target pose.
