Khurram Azeem Hashmi

According to our database, Khurram Azeem Hashmi authored at least 14 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

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

Object Detection with Transformers: A Review.

Tahira Shehzadi, Khurram Azeem Hashmi, Didier Stricker, Muhammad Zeshan Afzal

CoRR, 2023

BoxMask: Revisiting Bounding Box Supervision for Video Object Detection.

Khurram Azeem Hashmi, Alain Pagani, Didier Stricker, Muhammad Zeshan Afzal

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Towards End-to-End Semi-Supervised Table Detection with Deformable Transformer.

Tahira Shehzadi, Khurram Azeem Hashmi, Didier Stricker, Marcus Liwicki, Muhammad Zeshan Afzal

Proceedings of the Document Analysis and Recognition - ICDAR 2023, 2023

FeatEnHancer: Enhancing Hierarchical Features for Object Detection and Beyond Under Low-Light Vision.

Khurram Azeem Hashmi, Goutham Kallempudi, Didier Stricker, Muhammad Zeshan Afzal

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

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

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

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

Spatio-Temporal Learnable Proposals for End-to-End Video Object Detection.

Khurram Azeem Hashmi, Didier Stricker, Muhammad Zeshan Afzal

Proceedings of the 33rd British Machine Vision Conference 2022, 2022

2021

Survey and Performance Analysis of Deep Learning Based Object Detection in Challenging Environments.

Muhammad Ahmed, Khurram Azeem Hashmi, Alain Pagani, Marcus Liwicki, Didier Stricker, Muhammad Zeshan Afzal

Sensors, 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

Guided Table Structure Recognition Through Anchor Optimization.

Khurram Azeem Hashmi, Didier Stricker, Marcus Liwicki, Muhammad Noman Afzal, Muhammad Zeshan Afzal

IEEE Access, 2021

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

2019

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

Proceedings of the Second International Workshop on Machine Learning, 2019