OpenCodePapers
handwritten-mathmatical-expression-1
Handwritten Mathmatical Expression Recognition
Results over time
Click legend items to toggle metrics. Hover points for model names.
Leaderboard
Show papers without code
Paper
Code
ExpRate
↕
ModelName
ReleaseDate
↕
Uni-MuMER: Unified Multi-Task Fine-Tuning of Vision-Language Model for Handwritten Mathematical Expression Recognition
✓ Link
77.94
Uni-MuMER
2025-05-29
PosFormer: Recognizing Complex Handwritten Mathematical Expression with Position Forest Transformer
✓ Link
60.94
PosFormer
2024-07-10
TAMER: Tree-Aware Transformer for Handwritten Mathematical Expression Recognition
✓ Link
60.26
TAMER
2024-08-16
NAMER: Non-Autoregressive Modeling for Handwritten Mathematical Expression Recognition
60.24
NAMER
2024-07-16
ICAL: Implicit Character-Aided Learning for Enhanced Handwritten Mathematical Expression Recognition
✓ Link
58.79
ICAL
2024-05-15
CoMER: Modeling Coverage for Transformer-based Handwritten Mathematical Expression Recognition
✓ Link
56.98
CoMER
2022-07-10
When Counting Meets HMER: Counting-Aware Network for Handwritten Mathematical Expression Recognition
✓ Link
56.15
CAN-ABM
2022-07-23
When Counting Meets HMER: Counting-Aware Network for Handwritten Mathematical Expression Recognition
✓ Link
56.06
CAN-DWAP
2022-07-23
TDv2: A Novel Tree-Structured Decoder for Offline Mathematical Expression Recognition
55.18
TDv2
2022-06-28
Syntax-Aware Network for Handwritten Mathematical Expression Recognition
✓ Link
53.6
SAN
2022-03-03
Handwritten Mathematical Expression Recognition via Attention Aggregation based Bi-directional Mutual Learning
✓ Link
52.92
ABM
2021-12-07
Handwritten Mathematical Expression Recognition with Bidirectionally Trained Transformer
✓ Link
52.31
BTTR
2021-05-06
Multi-Scale Dense Networks for Resource Efficient Image Classification
✓ Link
50.1
DenseWAP-MSA
2017-03-29
A Tree-Structured Decoder for Image-to-Markup Generation
✓ Link
48.5
TD
Multi-Scale Dense Networks for Resource Efficient Image Classification
✓ Link
47.5
DenseWAP
2017-03-29
Watch, attend and parse: An end-to-end neural network based approach to handwritten mathematical expression recognition
✓ Link
44.55
WAP
2017-07-01