Search Results for author:
Found 25 papers, 12 papers with code
Merge and Recognize: A Geometry and 2D Context Aware Graph Model for Named Entity Recognition from Visual Documents
By incorporating geometry information from visual documents into our model, richer 2D context information is generated to improve document representations.
Understanding Gender Bias in Knowledge Base Embeddings
To exemplify the potential applications of our study, we also present two strategies (by adding and removing KB triples) to mitigate gender biases in KB embeddings.
An End-to-End OCR Text Re-organization Sequence Learning for Rich-text Detail Image Comprehension
Nowadays rich description on detail images help users know more about the commodities.
LayoutLLM: Layout Instruction Tuning with Large Language Models for Document Understanding
The core of LayoutLLM is a layout instruction tuning strategy, which is specially designed to enhance the comprehension and utilization of document layouts.
LORE++: Logical Location Regression Network for Table Structure Recognition with Pre-training
We model TSR as a logical location regression problem and propose a new TSR framework called LORE, standing for LOgical location REgression network, which for the first time regresses logical location as well as spatial location of table cells in a unified network.
Vision Grid Transformer for Document Layout Analysis
Document pre-trained models and grid-based models have proven to be very effective on various tasks in Document AI.
Ranked #1 on
Document Layout Analysis
on PubLayNet val
LISTER: Neighbor Decoding for Length-Insensitive Scene Text Recognition
The diversity in length constitutes a significant characteristic of text.
GeoLayoutLM: Geometric Pre-training for Visual Information Extraction
Additionally, novel relation heads, which are pre-trained by the geometric pre-training tasks and fine-tuned for RE, are elaborately designed to enrich and enhance the feature representation.
Ranked #1 on
Key Information Extraction
on CORD
LORE: Logical Location Regression Network for Table Structure Recognition
Table structure recognition (TSR) aims at extracting tables in images into machine-understandable formats.
ESceme: Vision-and-Language Navigation with Episodic Scene Memory
Vision-and-language navigation (VLN) simulates a visual agent that follows natural-language navigation instructions in real-world scenes.
Modeling Video As Stochastic Processes for Fine-Grained Video Representation Learning
Specifically, we enforce the embeddings of the frame sequence of interest to approximate a goal-oriented stochastic process, i. e., Brownian bridge, in the latent space via a process-based contrastive loss.
Cross-Modal Contrastive Learning for Robust Reasoning in VQA
For each positive pair, we regard the images from different graphs as negative samples and deduct the version of multi-positive contrastive learning.
Bi-VLDoc: Bidirectional Vision-Language Modeling for Visually-Rich Document Understanding
Multi-modal document pre-trained models have proven to be very effective in a variety of visually-rich document understanding (VrDU) tasks.
Bypass Network for Semantics Driven Image Paragraph Captioning
Most existing methods model the coherence through the topic transition that dynamically infers a topic vector from preceding sentences.
Visual Superordinate Abstraction for Robust Concept Learning
Concept learning constructs visual representations that are connected to linguistic semantics, which is fundamental to vision-language tasks.
FAVER: Blind Quality Prediction of Variable Frame Rate Videos
Video quality assessment (VQA) remains an important and challenging problem that affects many applications at the widest scales.
Decoupling Visual-Semantic Feature Learning for Robust Scene Text Recognition
As a result, the learning of semantic features is prone to have a bias on the limited vocabulary of the training set, which is called vocabulary reliance.
SentiPrompt: Sentiment Knowledge Enhanced Prompt-Tuning for Aspect-Based Sentiment Analysis
We inject sentiment knowledge regarding aspects, opinions, and polarities into prompt and explicitly model term relations via constructing consistency and polarity judgment templates from the ground truth triplets.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+3
Inference for High Dimensional Censored Quantile Regression
To our knowledge, there is little work available to draw inference on the effects of high dimensional predictors for censored quantile regression.
Pouring Dynamics Estimation Using Gated Recurrent Units
One of the most commonly performed manipulation in a human's daily life is pouring.
Classifying States of Cooking Objects Using Convolutional Neural Network
Automated cooking machine is a goal for the future.
Progressive Localization Networks for Language-based Moment Localization
The language-based setting of this task allows for an open set of target activities, resulting in a large variation of the temporal lengths of video moments.
Syntax-Aware Action Targeting for Video Captioning
Existing methods on video captioning have made great efforts to identify objects/instances in videos, but few of them emphasize the prediction of action.
Hierarchical Bilinear Pooling for Fine-Grained Visual Recognition
Fine-grained visual recognition is challenging because it highly relies on the modeling of various semantic parts and fine-grained feature learning.
Coarse-to-Fine Salient Object Detection with Low-Rank Matrix Recovery
Low-Rank Matrix Recovery (LRMR) has recently been applied to saliency detection by decomposing image features into a low-rank component associated with background and a sparse component associated with visual salient regions.
