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Found 8 papers, 3 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.
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.
Deep Adaptive Temporal Pooling for Activity Recognition
Specifically, using frame-level features, DATP regresses importance of different temporal segments and generates weights for them.
Defense Against Adversarial Attacks with Saak Transform
Therefore, we propose a Saak transform based preprocessing method with three steps: 1) transforming an input image to a joint spatial-spectral representation via the forward Saak transform, 2) apply filtering to its high-frequency components, and, 3) reconstructing the image via the inverse Saak transform.
Truly Multi-modal YouTube-8M Video Classification with Video, Audio, and Text
Beyond that, we extend the original competition by including text information in the classification, making this a truly multi-modal approach with vision, audio and text.
On Classification of Distorted Images with Deep Convolutional Neural Networks
Image blur and image noise are common distortions during image acquisition.
Egocentric Activity Recognition with Multimodal Fisher Vector
With the increasing availability of wearable devices, research on egocentric activity recognition has received much attention recently.
