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Found 10 papers, 0 papers with code
Progressive Evidence Refinement for Open-domain Multimodal Retrieval Question Answering
Firstly, utilizing compressed evidence features as input to the model results in the loss of fine-grained information within the evidence.
Homogeneous Multi-modal Feature Fusion and Interaction for 3D Object Detection
To address these problems, we construct the homogeneous structure between the point cloud and images to avoid projective information loss by transforming the camera features into the LiDAR 3D space.
Progressive Scene Text Erasing with Self-Supervision
Scene text erasing seeks to erase text contents from scene images and current state-of-the-art text erasing models are trained on large-scale synthetic data.
Cross-Domain Document Layout Analysis via Unsupervised Document Style Guide
Our framework is an unsupervised document layout analysis framework.
Document Layout Analysis with Aesthetic-Guided Image Augmentation
To measure the proposed image layer modeling method, we propose a manually-labeled non-Manhattan layout fine-grained segmentation dataset named FPD.
Document Image Layout Analysis via Explicit Edge Embedding Network
Layout analysis from a document image plays an important role in document content understanding and information extraction systems.
A Survey of Human-in-the-loop for Machine Learning
Humans can provide training data for machine learning applications and directly accomplish tasks that are hard for computers in the pipeline with the help of machine-based approaches.
Scene Text Recognition with Temporal Convolutional Encoder
In this paper, we study text recognition framework by considering the long-term temporal dependencies in the encoder stage.
Edge-Aware Deep Image Deblurring
In this paper, we resort to human visual demands of sharp edges and propose a two-phase edge-aware deep network to improve deep image deblurring.
