Search Results for author:
Found 7 papers, 5 papers with code
Perception and Semantic Aware Regularization for Sequential Confidence Calibration
In this work, we find tokens/sequences with high perception and semantic correlations with the target ones contain more correlated and effective information and thus facilitate more effective regularization.
A large-scale dataset for end-to-end table recognition in the wild
To this end, we propose a new large-scale dataset named Table Recognition Set (TabRecSet) with diverse table forms sourcing from multiple scenarios in the wild, providing complete annotation dedicated to end-to-end TR research.
Disentangling Writer and Character Styles for Handwriting Generation
In light of this, we propose to disentangle the style representations at both writer and character levels from individual handwritings to synthesize realistic stylized online handwritten characters.
Spatial Attention and Syntax Rule Enhanced Tree Decoder for Offine Handwritten Mathematical Expression Recognition
In this paper, we propose a novel model called Spatial Attention and Syntax Rule Enhanced Tree Decoder (SS-TD), which is equipped with spatial attention mechanism to alleviate the prediction error of tree structure and use syntax masks (obtained from the transformation of syntax rules) to constrain the occurrence of ungrammatical mathematical expression.
AGTGAN: Unpaired Image Translation for Photographic Ancient Character Generation
We evaluate our approach on the photographic ancient character datasets, e. g., OBC306 and CSDD.
Context-Aware Selective Label Smoothing for Calibrating Sequence Recognition Model
Despite the success of deep neural network (DNN) on sequential data (i. e., scene text and speech) recognition, it suffers from the over-confidence problem mainly due to overfitting in training with the cross-entropy loss, which may make the decision-making less reliable.
Complex Handwriting Trajectory Recovery: Evaluation Metrics and Algorithm
Many important tasks such as forensic signature verification, calligraphy synthesis, etc, rely on handwriting trajectory recovery of which, however, even an appropriate evaluation metric is still missing.
