Feedback Learning: Automating the Process of Correcting and Completing the Extracted Information. - Khurram Azeem Hashmi; Rakshith Bymana Ponnappa; Syed Saqib Bukhari; Martin Jenckel; Andreas Dengel 001 (WML@ICDAR, 2019)

Current Status and Performance Analysis of Table Recognition in Document Images With Deep Neural Networks. - Khurram Azeem Hashmi; Marcus Liwicki; Didier Stricker; Muhammad Adnan Afzal; Muhammad Ahtsham Afzal; Muhammad Zeshan Afzal (IEEE Access, 2021)

Guided Table Structure Recognition Through Anchor Optimization. - Khurram Azeem Hashmi; Didier Stricker; Marcus Liwicki; Muhammad Noman Afzal; Muhammad Zeshan Afzal (IEEE Access, 2021)

CasTabDetectoRS: Cascade Network for Table Detection in Document Images with Recursive Feature Pyramid and Switchable Atrous Convolution. - Khurram Azeem Hashmi; Alain Pagani; Marcus Liwicki; Didier Stricker; Muhammad Zeshan Afzal (J. Imaging, 2021)

Survey and Performance Analysis of Deep Learning Based Object Detection in Challenging Environments. - Muhammad Ahmed 002; Khurram Azeem Hashmi; Alain Pagani; Marcus Liwicki; Didier Stricker; Muhammad Zeshan Afzal (Sensors, 2021)

Spatio-Temporal Learnable Proposals for End-to-End Video Object Detection. - Khurram Azeem Hashmi; Didier Stricker; Muhammad Zeshan Afzal (BMVC, 2022)

Toward Semi-Supervised Graphical Object Detection in Document Images. - Goutham Kallempudi; Khurram Azeem Hashmi; Alain Pagani; Marcus Liwicki; Didier Stricker; Muhammad Zeshan Afzal (Future Internet, 2022)

Exploiting Concepts of Instance Segmentation to Boost Detection in Challenging Environments. - Khurram Azeem Hashmi; Alain Pagani; Marcus Liwicki; Didier Stricker; Muhammad Zeshan Afzal (Sensors, 2022)

Attention-Guided Disentangled Feature Aggregation for Video Object Detection. - Shishir Muralidhara; Khurram Azeem Hashmi; Alain Pagani; Marcus Liwicki; Didier Stricker; Muhammad Zeshan Afzal (Sensors, 2022)

FeatEnHancer: Enhancing Hierarchical Features for Object Detection and Beyond Under Low-Light Vision. - Khurram Azeem Hashmi; Goutham Kallempudi; Didier Stricker; Muhammad Zeshan Afzal (ICCV, 2023)

Towards End-to-End Semi-Supervised Table Detection with Deformable Transformer. - Tahira Shehzadi; Khurram Azeem Hashmi; Didier Stricker; Marcus Liwicki; Muhammad Zeshan Afzal (ICDAR (2), 2023)

BoxMask: Revisiting Bounding Box Supervision for Video Object Detection. - Khurram Azeem Hashmi; Alain Pagani; Didier Stricker; Muhammad Zeshan Afzal (WACV, 2023)

Object Detection with Transformers: A Review. - Tahira Shehzadi; Khurram Azeem Hashmi; Didier Stricker; Muhammad Zeshan Afzal (CoRR, 2023)

Bridging the Performance Gap between DETR and R-CNN for Graphical Object Detection in Document Images. - Tahira Shehzadi; Khurram Azeem Hashmi; Didier Stricker; Marcus Liwicki; Muhammad Zeshan Afzal (CoRR, 2023)

Sparse Semi-DETR: Sparse Learnable Queries for Semi-Supervised Object Detection. - Tahira Shehzadi; Khurram Azeem Hashmi; Didier Stricker; Muhammad Zeshan Afzal (CVPR, 2024)

UnSupDLA: Towards Unsupervised Document Layout Analysis. - Talha Uddin Sheikh; Tahira Shehzadi; Khurram Azeem Hashmi; Didier Stricker; Muhammad Zeshan Afzal (DAS, 2024)

Beyond Boxes: Mask-Guided Spatio-Temporal Feature Aggregation for Video Object Detection. - Khurram Azeem Hashmi; Talha Uddin Sheikh; Didier Stricker; Muhammad Zeshan Afzal (WACV, 2025)