https://github.com/HCIILAB/MTHv2_Datasets_Release
공식 코드Joint Layout Analysis, Character Detection and Recognition for Historical Document Digitization
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Joint Layout Analysis, Character Detection and Recognition for Historical Document Digitization
SegHist: A General Segmentation-based Framework for Chinese Historical Document Text Line Detection
Real-Time Salient Closed Boundary Tracking via Line Segments Perceptual Grouping
Real-Time Salient Closed Boundary Tracking via Line Segments Perceptual Grouping
Enhancing Soccer Camera Calibration Through Keypoint Exploitation
LINEA: Fast and Accurate Line Detection Using Scalable Transformers
A Two-Stage Method for Text Line Detection in Historical Documents
iCurb: Imitation Learning-based Detection of Road Curbs using Aerial Images for Autonomous Driving
READ-BAD: A New Dataset and Evaluation Scheme for Baseline Detection in Archival Documents
BST: Badminton Stroke-type Transformer for Skeleton-based Action Recognition in Racket Sports
UTRNet: High-Resolution Urdu Text Recognition In Printed Documents
SEMv3: A Fast and Robust Approach to Table Separation Line Detection
SOLD2: Self-supervised Occlusion-aware Line Description and Detection
DeepLSD: Line Segment Detection and Refinement with Deep Image Gradients
CmdCaliper: A Semantic-Aware Command-Line Embedding Model and Dataset for Security Research
Semantic Line Detection Using Mirror Attention and Comparative Ranking and Matching
Harmonious Semantic Line Detection via Maximal Weight Clique Selection
LSDNet: Trainable Modification of LSD Algorithm for Real-Time Line Segment Detection
The Impact of Semi-Supervised Learning on Line Segment Detection
Key Points Estimation and Point Instance Segmentation Approach for Lane Detection
Key Points Estimation and Point Instance Segmentation Approach for Lane Detection
MEM: Multi-Modal Elevation Mapping for Robotics and Learning
EVOLIN Benchmark: Evaluation of Line Detection and Association
Deep Learning for Detection and Localization of B-Lines in Lung Ultrasound
PageNet: Towards End-to-End Weakly Supervised Page-Level Handwritten Chinese Text Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.