9 citations · 27 across the 13 of their papers we have counts for
13 papers
Towards Improving Document Understanding: An Exploration on Text-Grounding via MLLMs
Yonghui Wang, Wengang Zhou, Hao Feng +2
In the field of document understanding, significant advances have been made in the fine-tuning of Multimodal Large Language Models (MLLMs) with instruction-following data. Neverthe…
DocPedia: Unleashing the Power of Large Multimodal Model in the Frequency Domain for Versatile Document Understanding
Hao Feng, Qi Liu, Hao Liu +4
This work presents DocPedia, a novel large multimodal model (LMM) for versatile OCR-free document understanding, capable of parsing images up to 2,5602,560 resolution. Unli…
Progressive Recurrent Network for Shadow Removal
Yonghui Wang, Wengang Zhou, Hao Feng +2
Single-image shadow removal is a significant task that is still unresolved. Most existing deep learning-based approaches attempt to remove the shadow directly, which can not deal w…
UniDoc: A Universal Large Multimodal Model for Simultaneous Text Detection, Recognition, Spotting and Understanding
Hao Feng, Zijian Wang, Jingqun Tang +4
In the era of Large Language Models (LLMs), tremendous strides have been made in the field of multimodal understanding. However, existing advanced algorithms are limited to effecti…
Sign Language Translation with Iterative Prototype
Huijie Yao, Wengang Zhou, Hao Feng +3
This paper presents IP-SLT, a simple yet effective framework for sign language translation (SLT). Our IP-SLT adopts a recurrent structure and enhances the semantic representation (…
SimFIR: A Simple Framework for Fisheye Image Rectification with Self-supervised Representation Learning
Hao Feng, Wendi Wang, Jiajun Deng +3
In fisheye images, rich distinct distortion patterns are regularly distributed in the image plane. These distortion patterns are independent of the visual content and provide infor…
Multi-Task Cross-Modality Attention-Fusion for 2D Object Detection
Huawei Sun, Hao Feng, Georg Stettinger +2
Accurate and robust object detection is critical for autonomous driving. Image-based detectors face difficulties caused by low visibility in adverse weather conditions. Thus, radar…
DocMAE: Document Image Rectification via Self-supervised Representation Learning
Shaokai Liu, Hao Feng, Wengang Zhou +3
Tremendous efforts have been made on document image rectification, but how to learn effective representation of such distorted images is still under-explored. In this paper, we pre…
Deep Unrestricted Document Image Rectification
Hao Feng, Shaokai Liu, Jiajun Deng +2
In recent years, tremendous efforts have been made on document image rectification, but existing advanced algorithms are limited to processing restricted document images, i.e., the…
Recurrent Generic Contour-based Instance Segmentation with Progressive Learning
Hao Feng, Keyi Zhou, Wengang Zhou +4
Contour-based instance segmentation has been actively studied, thanks to its flexibility and elegance in processing visual objects within complex backgrounds. In this work, we prop…
Geometric Representation Learning for Document Image Rectification
Hao Feng, Wengang Zhou, Jiajun Deng +2
In document image rectification, there exist rich geometric constraints between the distorted image and the ground truth one. However, such geometric constraints are largely ignore…
Cross-modal Learning of Graph Representations using Radar Point Cloud for Long-Range Gesture Recognition
Souvik Hazra, Hao Feng, Gamze Naz Kiprit +5
Gesture recognition is one of the most intuitive ways of interaction and has gathered particular attention for human computer interaction. Radar sensors possess multiple intrinsic…
DocTr: Document Image Transformer for Geometric Unwarping and Illumination Correction
Hao Feng, Yuechen Wang, Wengang Zhou +2
In this work, we propose a new framework, called Document Image Transformer (DocTr), to address the issue of geometry and illumination distortion of the document images. Specifical…